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CLINICAL SYNTHESIS   |    
Improving the Quality of Psychiatric Care: Aligning Research, Policy, and Practice
Kelli Jane K. Harding, M.D.; Harold Alan Pincus, M.D.
FOCUS 2011;9:153-164.
View Author and Article Information

CME Disclosure

Kelli Jane K. Harding, M.D., Department of Psychiatry, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York State Psychiatric Institute, New York Presbyterian Hospital, New York, NY.

Reports no competing interests.

Harold Alan Pincus, M.D., Department of Psychiatry, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York State Psychiatric Institute, New York Presbyterian Hospital, New York, NY and RAND, Pittsburgh, PA.

Reports no competing interests.

Address correspondence to Dr. Kelli Harding, Columbia University, Department of Psychiatry, 1051 Riverside Dr., Unit 125, New York, NY 10032; e-mail: kjh2104@columbia.edu

An erratum to this article has been published | view the erratum

The aim of this article is to assist psychiatrists in meeting their responsibilities to better understand their patients and improve the quality of medical care that they receive. The importance of quality, the state of health care quality, and health care aims and expectations are reviewed. In addition, integration of strategies to build a stronger infrastructure to support the delivery of high-quality mental health care is discussed at both the clinical and systems/policy levels. At the systems/policy level the following are addressed: 1) how to achieve consensus and greater specificity on standard elements, methods, assessment tools, and treatment guidelines and provide applications to implement them in clinical practice using health information technology; 2) how to establish methods to measure the quality of mental health care delivered to patients and provide support and incentives for clinicians and organizations to adopt care improvement strategies, including building the measurement and monitoring infrastructure, designing improvement incentives, providing training/support for organizational improvement methods, and updating clinical training/accreditation/certification standards; and 3) how to develop leadership and resources to expand the evidence base to have a direct impact on health care decision making by patients, clinicians, and policymakers (i.e., comparative effectiveness research). Although the 2010 health care reform legislation (Patient Protection and Affordable Care Act) emphasizes health care insurance coverage issues, it contributes further strategies to help transform U.S. health care delivery system to improve quality and reduce cost. This article offers aid to clinicians for navigating and participating in the professional changes ahead.

Abstract Teaser
Figures in this Article

The passage of the landmark 2010 Patient Protection and Affordable Care Act (ACA) and its provisions for supporting quality drew attention to ongoing health care value trends in the United States; however, quality issues in health care are not new. More than a decade has passed since the national dialogue on shortfalls in care delivery began with the landmark Institute of Medicine (IOM) series To Err Is Human: Building a Safer Health System (1) and Crossing the Quality Chasm: A New Health System for the 21st Century (2). These initial reports documented the “chasm” between the medical care that should be and is given in the United States, including how nearly 100,000 people die each year as a result of presumably preventable medical errors (1). In addition, the series highlighted significant gaps between research, policy, and practice, with a disappointing 17-year lag in the translation of biomedical research into actual clinical practice, the so-called “bench to bedside” delay (2).

Despite having the most expensive health care system in the world, accounting now for 17.3% of the gross domestic product (GDP) (3), health care in the United States repeatedly falls short on expected results (4). For instance, a World Health Organization (WHO) report in 2000 found that the United States ranked 37th on health care quality (France ranked first) using measures such as health equality, life expectancy, fairness in financial contribution, health performance indicators, and health expenditures per capita (5). A 2007 Commonwealth Fund Report ranked the U.S. health care system last or next-to-last on five dimensions of a high-performance health system (quality, access, efficiency, equity, and healthy lives) compared with that of five other developed nations—Australia, Canada, Germany, New Zealand, and the United Kingdom (4). As former WHO Director-General Dr. Gro Harlem Brundtland said, “the health and wellbeing of people around the world depend critically on the performance of the health systems that serve them. Yet there is wide variation in performance, even among countries with similar levels of income and health expenditure” (6).

The disparity between optimal and actual medical care is widespread across conditions (preventive, acute, and chronic), health care settings (inpatient and outpatient), patient populations (age, ethnicity, and socioeconomic status), and geographic areas (79). Variations in health care delivery, as shown in the Dartmouth Atlas of Health Care, are not simply due to how sick people are or how much medical care they receive. In other words, more care does not equal better care (10). Chronic diseases are particularly vulnerable to variation: patients are susceptible to underuse, overuse, and inappropriate use of medical services, with an estimated chance of only 55% of getting recommended care (8). Quality shortfalls demonstrate the need for fundamental change of health care delivery in America. As noted in the IOM Crossing the Quality Chasm report, “Quality problems occur typically not because of failure of goodwill, knowledge, effort, or resources devoted to health care, but because of fundamental shortcomings in the ways care is organized.” In essence, problems are so widespread that trying harder within the current system is not enough. System-wide change is needed (2).

In the United States it is unclear who has primary responsibility for health care quality. A fragmented “alphabet soup” of stakeholder agencies and organizations, including private insurers, the government, and consumer groups, use a variety of performance measures to examine quality from each of their unique perspectives. Despite much activity in the development of health and mental health quality indicators, efforts in the United States lack coordination. At present no single entity oversees or coordinates health care quality improvement efforts or organizes incorporation of best practices based on performance findings (11).

No matter how the quality improvement effort is organized, physicians hold a key leadership role from their own practices to the national arena. The Accreditation Council for Graduate Medical Education (ACGME) core competencies of professionalism, practiced-based learning and improvement (PBLI), and systems-based practice (SBP) (12) redefined physician proficiency beyond biomedical research alone. Understanding and improving the current state of health care quality in their own practices is the first step in integrating expectations across these competencies.

The IOM Crossing the Quality Chasm report listed six key aims for improvement in health care quality (2). These key aims, that health care should be safe, timely, effective, efficient, equitable, and patient centered, are central to health care quality improvement:

  • Safe , meaning avoiding injuries to patients from the care intended to help them.

  • Timely , indicating reduced waits and harmful delays for both those who receive and those who give care.

  • Effective , implying the provision of services based on scientific knowledge to all who could benefit and refraining from providing services to those not likely to benefit (i.e., avoiding underuse and overuse, respectively).

  • Efficient , demonstrating the importance of avoiding waste, including waste of equipment, supplies, ideas, and energy (i.e., duplication of services).

  • Equitable , meaning providing care that does not vary in quality because of personal characteristics such as gender, ethnicity, geographic location, and socioeconomic status.

  • Patient-centered , signifying the importance of providing care that is respectful of and responsive to individual patient preferences, needs, and values.

Thus, the goal is to ensure that health care promotes patient values in guiding clinical decisions. The IOM report also provided 10 rules for patient/consumer expectations of their health care system (Figure 1).

 
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Figure 1. The 10 Rules for Patient/consumer Expectations of Their Health Care System

[Adapted from Institute of Medicine: To Err Is Human: Building a Safer Health System. Washington DC, National Academy Press, 2000; and Berwick DM: A user's manual for the IOM's ‘Quality Chasm’ report. Health Aff (Millwood) 2002; 21(3):80–90.]

As is true in medicine in general, a disparity exists between the mental health care people could receive and the care they actually do receive. For instance, evidence-based approaches for treating depression, such as the chronic care model described below, are effective (13), yet are rarely used in practice (14). Furthermore. the rate of improvement on quality measures in mental health trails behind gains made in other areas of medicine, such as controlling high blood pressure and β-blocker treatment after a heart attack (7). The Institute of Medicine's 2006 Improving the Quality of Health Care for Mental and Substance-Use Conditions: Quality Chasm Series identified several key areas of quality problems in mental heath. These included 1) failure to provide care consistent with scientific evidence, 2) unnecessary variations in care (including disparities in care associated with race/ethnicity), 3) lack of access to care, and 4) unsafe care (15, pp 4–6, 3236).

  • Failure to provide care consistent with scientific evidence 

    A review of studies from 1992 to 2000 demonstrated across conditions, such as depression, bipolar disorder, panic disorder, schizophrenia, and alcohol withdrawal, only 27% clinician adherence to established clinical guidelines (16). In 2003, patients with alcohol dependence were found to receive only 10.5% of recommended care (8). The yearly Health Plan Employer Data and Information Set report on the state of U.S. health care quality, developed by the National Committee for Quality Assurance and used by more than 90% of America's managed health care plans, measures performance on important dimensions of care and service. Their 2010 report indicated that the majority of patients with commercial insurance in whom a first episode of major depression was diagnosed and who were given antidepressant medication were about as likely to receive appropriate initial treatment (i.e., taking antidepressant medication for at least 12 weeks) in 2009 as in 1999 (62.9% in 2009 versus 58.8% in 1999). In addition, the percentage of Medicaid recipients with newly diagnosed depression receiving effective ongoing treatment (i.e., taking antidepressant medication for at least 6 months) also was little changed from 2001 (30.0%) to 2009 (33.0%). Furthermore, it is known that the number of days between hospital discharge and a follow-up visit is a significant predictor of treatment nonadherence (17) and identifies patients in need of additional interventions before they reach a crisis point or need for rehospitalization (18). Among Medicare recipients discharged from psychiatry hospitalizations in 2009, only 37.3% had an outpatient follow-up visit within 7 days (the same rate as in 2001), and 54.8% had a visit within 30 days (decreased  from 60.6% in 2001) (7).

  • Unnecessary variations in care 

    Unnecessary variations in care, particularly relating to race, ethnicity, and age have been known to exist in psychiatry for some time. For instance, misdiagnosis is more likely to occur in black Americans, and they are more likely to receive antipsychotic medications at higher doses without clear indications (1921). Schizophrenia is more likely to be overdiagnosed and depression underdiagnosed in black individuals; however, when diagnoses are based on more structured clinical interviews, rates of these illnesses were similar to those in their white counterparts (22). Other ethnic minority groups and children also appear vulnerable to inappropriate variations in care, including widespread use of antipsychotic medications for off-label purposes (2325).

  • Lack of access to care 

    Accessing help for mental health problems remains problematic for many Americans. In the United States, more than 15% of the overall disease burden is attributable to mental illnesses (26), and the economic burden of serious mental illness, including the cost of health services, loss of earnings, and disability benefits, is estimated to be $317 billion (27). Major depression alone accounts for nearly half of lost productive time, costing more than $30 billion per year (28). However, mental health care is not readily available to those in need (2931). Factors beyond health insurance and ability to pay are involved in the inability to access mental health care (32, 33), including structural barriers  (uncertainty of how to access services) and attitudinal barriers  (i.e., the belief that the problem would get better on its own, concerns about efficacy, the stigma/shame of mental illness, fears of hospitalization, or fears of being forced to take medication) (30, 34).

    Race and ethnicity are two factors that illustrate the complex nature of issues relating to access. A large epidemiologic study showed that black adults are roughly two times less likely than white respondents to receive treatment for mood and anxiety disorders, even after adjustment for differences in income, education, and severity of illness. The study also showed that white respondents with drug use disorders were significantly less likely than black respondents to receive treatment for a drug problem (35). Considering that barriers to access are particularly important given 2009 data showing that 20.9 million people, or 8.3% of the U.S. population aged 12 years or older, had an unmet need for treatment for an illicit drug or alcohol use problem (31).

  • Unsafe care 

    Unsafe care, such as medication errors or interventions with a high risk of harm (i.e., restraints), is known to cause significant morbidity and mortality in general health care; however, few studies have looked at the incidence, nature, predictors, and prevention of errors that occur in mental health treatment settings (36, 37). The limited available data suggest that medication errors and adverse drug events are common in psychiatric hospitals and occur with the same frequency as they do in general hospitals (38). What little is known about psychiatric medical errors primarily relates to inpatient services and the use of seclusion and restraint (36, 39). The lack of data in itself is cause for concern and in part may relate to the failure to properly educate practitioners in the mental health field (40). As noted by Grasso et al. (41), “Psychiatrists may not be sufficiently aware of the harm caused by errors, methodological issues regarding error detection, the validity of reported medication error rates, and the challenge of creating a nonpunitive error-reporting culture.”

    Lucian Leape, in his landmark 1994 JAMA  article on medical errors, called for the end of the “guilt culture” approach to mistakes, i.e., focusing on who made the error, and instead advocated an approach to determine what system failure allowed a well-trained and well-intentioned professional to make a mistake (42). Reframing errors as “bad systems, not bad people” has dramatically reduced errors in industries such as commercial aviation and nuclear power generation, and there is some evidence that this paradigm is taking hold throughout medicine (43). In psychiatry, the state of Pennsylvania reframed use of seclusion and restraint as a “treatment failure” indicator for its state hospital system and through quality improvement initiatives was able to dramatically reduce use of these interventions (from 107.9 hours per 1,000 patient days in 1993 to 2.72 hours per 1,000 patient days in 2000) (44). Implementation of these types of innovations indicate that quality improvement is feasible in mental health.

The 2006 IOM report recommended a five-part strategy to build a stronger infrastructure to support the delivery of high-quality mental health and substance use (MH/SU) care. This includes 1) more coordination in filling gaps in the evidence base, 2) a stronger, more coordinated, and evidence-based approach to disseminating evidence to clinicians, 3) improved diagnosis and assessment strategies, 4) a stronger infrastructure for measuring and reporting the quality of MH/SU care, and 5) support for quality improvement practices at the sites of MH/SU care (15). In this article we discuss the integration of these strategies first at the clinical level and second at the systems/policy level.

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Clinical level

Whether in outpatient or inpatient specialty mental health or general medical settings, psychiatrists and other mental health professionals must learn and apply 1) evidence-based strategies for assessment and treatment in the care of their patients and 2) quality improvement methods at the locus of care. These approaches provide a strategy for improving the quality of patient care directly at the clinical level.

If mental health care is to hold to the industry principle, “You can't improve what you can't measure,” standardized measures need to be introduced for clinical evaluations and treatment. Systematic measures help clarify treatment goals, track patient progress over time, and adjust interventions continuously based on results to optimize outcomes (45). For example, the management of chronic medical conditions, including hypertension, asthma, congestive heart failure, and MH/SU conditions (i.e., major depression, bipolar disorder, alcohol abuse, and schizophrenia) requires systematic longitudinal clinical measurement and adjustment of treatment strategies based on the findings from those measures (i.e., measurement-based care) (46).

Despite routine use of measurement-based care in psychiatric research, the use of measurement has not permeated day-to-day patient care to assist with diagnosis and monitor treatment response, decreasing the likelihood of scientific knowledge being applied to practice (46). Reliable instruments for identifying and assessing psychiatric conditions are available but are not widely applied. For instance, structured interviews increase the detection of psychiatric conditions (47). Furthermore, even though a diligent step-by-step approach to depression treatment produces better outcomes and prognoses than usual care (48, 49), validated measures for tracking depressive symptoms, such as the clinician-guided Patient Health Questionnaire (PHQ-9) or self-report Beck Depression Inventory (BDI), are not typically used to guide care.

In addition to the incorporation of standard measures, to improve the quality of care, the practice infrastructure for mental health services needs strengthening. One such strategy is incorporation of the principles of the chronic care model or “mental health home” (50) in existing practices. The patient-centered chronic care model (5153) (Figure 2) is a conceptual framework used by numerous health organizations for implementation of quality improvement initiatives (53). The model seeks to achieve better treatment outcomes through improved interactions between prepared patients/families and a proactive care team that is patient centered, coordinated, longitudinal, efficient, safe, and evidence based. These relationships are supported by a practice infrastructure that includes self-management support, clinical information systems, decision support, and delivery system design for chronic illness care, which are in turn supported by policies and leadership at the health system level. Further elaborations on this concept, the “patient-centered or advanced medical (or health) home” (54), are incorporated into health care reform strategies and are also being applied to mental health care (55).

 

Chronic care models encourage adapting evidence-based guidelines into routine clinical decision making to help assure that consumers are getting the best possible care with currently available treatments. Although there are electronic tools to facilitate this practice (discussed below), one immediate practice clinicians can adopt is engaging in shared decision making and self-management with patients. In these frameworks, patient and provider are both considered experts, a concept that has been shown to have positive mental health effects (56). Not unlike home blood pressure monitoring (57), people with psychiatric conditions can systematically follow their own symptoms on self-report measures for discussions with providers during visits. Consumers and their families can lead the change with their doctors, starting now by downloading and filling out self-report measures [see http://www.depressionprimarycare.org/clinicians/toolkits/ (MacArthur Foundation) or http://impact-uw.org/tools/ (Project IMPACT)].

Also incorporated into these concepts is the use of team-based care management (58) to coordinate care activities between appointments, such as phone calls, e-mail reminders, and monitoring measures. With physician oversight, the implementation of nonphysician care managers has shown to significantly improve control of depression and other medical diseases, as well as patient satisfaction (59), which has been shown to predict enhanced self-care and more favorable outcomes (60).

Although hiring a care manager is a financial challenge for solo-practice psychiatrists, partnering with other practices could facilitate a quality infrastructure with shared personnel and resources. As an alternative, solo practitioners could contract with an outside Web- or phone-based care management service. For instance, the Veterans Affairs system uses remote behavioral health telephone care coordinators to regularly check in with depressed patients and relay information back to practitioners (61). The use of care managers along with electronic medical records (EMRs) or even simply a spreadsheet is particularly helpful for organizing and maintaining a patient registry, a system that allows tracking of patient outcomes with similar diseases, such as depression (62).

It is also critical that psychiatrists take a leadership role in applying systematic quality improvement methods at the point of care. Approaches such as Plan–Do–Study–Act (PDSA), Lean Manufacturing, Six Sigma, and the Toyota Production System (63) adapted from fields such as systems engineering, aerospace, and manufacturing, are being applied across medicine to change care processes and improve care. For example, PDSA (or Deming) cycles (64, 65) are based on the scientific method (hypothesis–experiment–evaluation) and involve a systematic Plan (a proposition for improvement), Do (actions taken toward the improvement), Study (use of measurement to determine the effects of the intervention), and Act (applying knowledge to further improve). PDSA cycles are an iterative process that allows clinician and practices an opportunity to improve the quality of care and become intimately familiar with the process of quality improvement through practice (66). There are a number of policy/systems level changes on the horizon that will encourage and support physicians in implementing improvement methods in their own practices.

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Policy/systems level

Improving the quality of mental health care is going to require initiation of a robust set of complementary policies aimed at multiple system levels (Figure 3).

 
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Figure 3.Preparing for the Future in Mental Health

(Reproduced with permission from Pincus HA: Crossing the quality chasm. Schizophr Bull 2010; 36:109–111. Copyright © The Author 2009. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.)

  • Achieve consensus and greater specificity on standard elements, methods, assessment tools, and treatment guidelines and provide applications to implement them in clinical practice using health information technology (HIT). 

    There is no agreement on a standard set of mental health “vital signs” or of which clinical measures to use in routine practice. Imagine seeing an internist who did not check blood pressure regularly for hypertensive care. Because this is considered a standard care expectation, something would seem amiss. Yet, what constitutes an expected mental health examination? Practice components, such as specific measures for clinical assessment, clinical decision algorithms and evidence-based interventions have not been specified and standardized in psychiatry.

    Evidence-based guidelines in mental health, as developed by professional associations or other groups, will need to include measurement as an expectation with explicit guidance on which assessment tools or treatments to use for whom and when. Psychiatric treatment guidelines (67), in part because of the current limited evidence base, are not specific and recommend that clinicians monitor treatment responses without sufficient detail about what this involves. Defining terms such as “moderate improvement” or “relapse” more specifically on a standard scale, such as a 35%–50% symptom reduction or 20% change in baseline, would reduce variability. Conservative initial parameters could be adjusted over time to reflect the growing evidence base, as is done with other chronic conditions such as hypertension, (68) and could help determine minimal remission and recovery standards for mental disorders.

    Mental health guidelines will also need to be more explicit about what constitutes adequate treatment with standardized protocols and preidentified decision points. For instance, in depression care, how long and at what dose is an adequate trial of an antidepressant before augmenting or switching? Structured guideline implementation, with clear algorithms and fidelity expectations, have been shown to improve the quality of provider performance and patient outcomes in depression care in both the Texas Medication Algorithm Project (TMAP) (49) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies (48).

    As is true in the rest of medicine, once measurement tools and clinical algorithms/guidelines are specified in mental health, they must be readily available to clinicians in a workflow-friendly way as part of EMRs, a building block of standardization. Clinical decision support systems (CDSS) built into EMRs can disseminate up-to-date clinical information required to deliver high-quality care at the point of contact. When created with user input, CDSS can facilitate incorporation of evidence-based guidelines into clinical practice. In the information age with thousands of medical journals available, keeping up on the literature on one's own is daunting. CDSS, if done correctly, can help, along with other technological aides. Computerized physician order entry (CPOE) and e-prescribing assist in minimizing errors and make it easier for clinicians to “do the right thing” (69).

    Another important potential advantage of applying HIT is the capacity to have all the necessary information about a patient's past history available at the point of care when critical decisions are made. For example, readily available information (e.g., on a secure Web site or credit card-like chip) could prevent repeat brain imaging and radiation exposure for patients presenting with psychosis in emergency department settings. In addition, easily accessible information about medication doses and laboratory findings could facilitate handoffs and minimize disruptions in care with transition between mental health providers or inpatient to outpatient psychiatry settings. At the same time, although medical information should be available when and where it is needed, it is essential that distribution of such information (and especially information related to mental health) be under the patient's control and be fully protected and secure.

    The American Recovery and Reinvestment Act of 2009 (ARRA) created a national agenda for HIT across medicine by designating $19 billion toward the adoption of HIT and EMRs into U.S. practice settings by 2014. In addition, physicians using a “certified” EHR, meaning it meets standards of meaningful use toward improving patient care (i.e., not for billing alone), are eligible for substantial incentives as of 2011 (70). A report released in January 2011 showed that 41% of all office-based physicians across specialties and 80% of the nation's hospitals intend to take advantage of federal incentive payments for adoption of certified EMRs (71). Unfortunately, nonphysician mental health providers and mental health and substance use clinical organizations were excluded from receiving the ARRA incentive payments. Mental health will need to be fully integrated into this information infrastructure.

  • Establish methods to measure the quality of mental health care delivered and provide support and incentives for clinicians and organizations to adopt care improvement strategies. 

    More specific guidelines not only need to be developed and integrated into tools to apply them at the point of care, but they also need to be translated into a quality measurement and monitoring infrastructure at the levels of consumers, clinics, health systems, health plans, and populations (72). Organizational support and quality improvement incentives reinforce learning to use measures and implementing quality care initiatives.

    • Building the measurement and monitoring infrastructure 

      Ultimately, the nation needs a comprehensive quality measurement and monitoring system across all of health care including strategies that are adapted to the needs of mental health care. A blueprint for such a system is provided in the 2010 IOM report on Provision of Mental Health Counseling Services under TRICARE  (73), which went somewhat beyond its formal charge to recommend implementation of a quality measurement and monitoring system across all military mental health services. (TRICARE is the Department of Defense's health care benefits program that serves all of the uniformed services and their families, comprising more than 9 million beneficiaries.) The report recommended development and application of quality measures to assess provider performance, monitoring of results, processes, and outcomes of care at all levels, and systematic and focused continued professional education.

      The overall recommendation for a comprehensive quality management system clearly extends well beyond TRICARE and is consistent with those suggested previously by the IOM as the components of a national quality measurement and reporting infrastructure. Identified care measures need translation into specific performance measures that are then piloted for their validity, reliability, feasibility, and cost. These performance measures would ideally be composed of data gathered during routine processes of care (e.g., electronic health records and insurance claims) rather than through a separate data collection process (74). The data would then need to be submitted to a repository, allowing for auditing to confirm that the performance measures were calculated accurately as specified. The results would then need to be analyzed and displayed in a format appropriate for intended audiences such as consumers, physicians, health systems, health plans, and quality oversight organizations. Although various disparate organizations in the public and private sector currently perform some of these functions, there are numerous gaps and redundancies that require a much more coordinated national approach.

    • Designing improvement incentives 

      Organizations, such as government, health plans, accreditation/regulatory agencies, coalitions of employers, and professional groups, can use a variety of incentives (e.g., financial and public reporting) to further motivate physicians to incorporate evidence-based practice models and standards of care (75). Across health care in general there are numerous initiatives linking the use of structure, process, and outcome measures to incorporate quality into the payment system. For instance, there are numerous “value-based” initiatives incorporated in the ACA that link payment to a bundling of services with adjustment for quality and efficiency that will need to be tailored for mental health care. These include the expansion of existing initiatives for Medicare value-based purchasing, such as physician self-reporting on designated quality measurements as well as nonpayment for iatrogenic hospital complications or services deemed not clinically necessary on chart review. Other value-based initiatives include bundling payments and the use of “accountable care organizations” to pay for a person's care needs over a period of time (76). Importantly, these initiatives apply funding models that have much greater flexibility than fee-for-service, allowing, for example, support of care and quality management activities.

      Other financial incentives include pay for performance (P4P) models that have developed throughout medicine using measures in areas such as inpatient/outpatient care, medication management, monitoring, consumer perceptions, and outcomes (77). Mental health lags behind the rest of medicine in P4P with one study in 2008 finding 24 existing programs in behavioral and mental health. Most of the programs identified primarily focus on depression care in a primary care setting (78). A particularly interesting P4P model is being implemented in Minnesota: the DIAMOND (Depression Improvement Across Minnesota Offering a New Direction) Project (79). Participating medical groups are initially rewarded for establishing a structure for applying evidence-based care and in the second phase are rewarded for actually implementing systematic longitudinal clinical measurement. In the third phase, an increasing proportion of rewards is based on improved outcomes for patients. Although P4P models are promising for implementing widespread adoption of quality measures and continuous improvement, as demonstrated by the ambitious and successful National Health Service program in England (80), there are limitations to the models of P4P. Evidence indicates that P4P often rewards those who have higher baseline performance (75) and if removed may cause a decline in quality (81). Therefore, it is important to link these efforts to enduring provider education and support.

    • Training/support for organizational improvement methods 

      Individual providers and organizations will need to learn how to implement improvement strategies at the locus of care and throughout the organization. Organizational readiness for change in specialty mental heath settings is influenced by leadership to shift the organizational climate and motivate staff for change (82). Making quality improvement a top organizational priority with dedicated resources is a common element of success in quality improvement (83). Training and financial support for organizational improvement methods help reduce variations in care and increase effective care delivery (84).

      Organizations such as the not-for-profit Institute for Health Care Improvement (IHI) have worked to “ensure the broadest possible adoption of best practices and effective innovations” (85) through identifying and testing new models in general health care. There is need for an organization such as the IHI to spearhead organizational change for mental health. One example in behavioral health is the University of Wisconsin-Madison's NIATx network, created in 2003, which aims to improve the “cost and effectiveness of the care delivery system” for people with mental illness and/or addiction and “remove barriers to treatment and recovery” for payers and providers (86).

    • Updating clinical training/accreditation/certification standards 

      The current mental heath workforce needs training to gain comfort using the tools of measurement and quality improvement. Unless they are involved in clinical research, practicing doctors and trainees are unlikely to have learned to incorporate measurement into routine care. Quality and measurement training, both cognitive (tested on examinations) and practical (application to practice), demonstrate the ACGME core competencies of professionalism, PBLI, and SBP. Educators across the spectrum from undergraduate, graduate, and continuing medical education need to incorporate training in these areas for future and current doctors. The American Board of Psychiatry and Neurology is actively moving this agenda forward by incorporating quality improvement programs into revised Maintenance of Certification by 2012, including best practice and guideline adherence by chart and patient/peer review and improvement plan implementation (87).

  • Develop leadership and resources to expand the evidence base to have a direct impact on health care decision making by patients, clinicians, and policymakers (i.e., comparative effectiveness research). 

    Comparing the benefits and harms of two approaches or interventions directly in actual practice is known as “comparative effectiveness research” (CER) or “patient-centered outcomes research” (88). CER incorporates strategies for designing and promoting research that contributes to both identifying and filling in knowledge gaps at both clinical and health systems levels. It also involves evaluation of quality improvement strategies and policies and rapidly synthesizing updates in knowledge to help clinicians, consumers, and policymakers make informed decisions.

    As part of the national ARRA, the IOM was asked to develop a list of initial national priorities for funds dedicated to comparative effectiveness across health care. Topics for mental health and substance use conditions constituted one of the largest “buckets” of the “top 100” national priorities. Among top national priorities were comparing the effectiveness of pharmacological treatment and behavioral interventions in managing major depressive disorders in diverse treatment settings, as well as comparing atypical antipsychotics and conventional pharmacological treatment for different indications. The IOM prioritized comparison of management strategies after a suicide attempt (e.g., inpatient psychiatric hospitalization, extended observation, partial hospitalization, or intensive outpatient care), in addition to different treatment approaches (e.g., integrating mental health care and primary care, improving consumer self-care, and a combination of integration and self-care) in avoiding early mortality and comorbidity among people with serious and persistent mental illness. Furthermore, the report stressed the importance of developing a CER framework capable of continuously incorporating new evidence as diseases and interventions evolve.

The passage of the 2010 health care reform legislation, including the 32 million Americans who are poised to gain access to health care in 2014, is creating a huge push to improve quality and value in general and mental health care. With this paradigm shift comes challenges unique to mental health as well as a great opportunity to provide better care and involve patients more in their own care. Furthermore, the focus on quality and value in health care delivery will expand and further redefine the general competencies of professionalism, problem-based learning and improvement, and systems-based care. The competencies were, in fact, created to ensure a professional's ability to practice “in the rapidly changing health care environment” (89). Their evolving use will enable clinicians to fully participate in quality improvement initiatives on the horizon and shift from a more individualistic patient care approach to a more public health interconnected model (90). In other words, the definition of what it means to be a “good doctor” has changed (91).

Commitment, leadership, and collaboration among mental health consumers as well as clinicians are necessary to improve quality at a clinical level and are equally critical for creating system change. Ongoing participation of such individuals with intimate knowledge of the challenges of care of patients with mental illnesses is essential to assure that these perspectives are incorporated by policymakers and administrators in ongoing system redesign and progressive quality improvement at multiple levels. Of course, approaches applied in general health will need to be tailored to reflect the unique aspects of psychiatric care. Nonetheless, implementation of the aims, rules, and strategies for redesign laid out by the IOM in Crossing the Quality Chasm, could transform the structure, processes, and outcomes of daily practice and improve the lives of individuals with mental disorders.

Institute of Medicine: To Err Is Human: Building a Safer Health System.  Washington DC,  National Academy Press, 2000
 
Institute of Medicine: Crossing the Quality Chasm: A New Health System for the 21st Century.  Washington, DC,  National Academy Press, 2001
 
Davis K, Schoen C, Stremikis K: Mirror Mirror on the Wall: How the Performance of the US Health Care System Compares Internationally. 2010 Update.  New York,  The Commonwealth Fund, 2010
 
World Health Organization: The World Health Report 2000—Health Systems: Improving Performance. http://www.who.int/whr/2000/en/
 
World Health Organization: World Health Organization Assesses the World's Health Systems. 2000. http://www.who.int/whr/2000/media_centre/press_release/en/index.html
 
National Committee for Quality Assurance: The state of health care quality. 2010. http://www.ncqa.org/tabid/836/Default.aspx
 
McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA: The quality of health care delivered to adults in the United States.  N Engl J Med 2003; 348:2635–2645
 
Asch SM, Kerr EA, Keesey J, Adams JL, Setodji CM, Malik S, McGlynn EA: Who is at greatest risk for receiving poor-quality health care?  N Engl J Med 2006; 354:1147–1156
 
Wennberg JE, Fisher, ES, Goodman DC, Skinner JS: Tracking the Care of Patients with Severe Chronic Illness. The Dartmouth Atlas of Health Care 2008.  Executive Summary .  Dartmouth, NH,  The Dartmouth Institute for Health Policy and Clinical Practice, 2008
 
Herbstman BJ, Pincus HA: Measuring mental healthcare quality in the United States: a review of initiatives.  Curr Opin Psychiatry 2009; 22:623–630
 
Accreditation Council for Graduate Medical Education: Common Program Requirements. Effective July 1, 2007. http://www.acgme.org/acWebsite/dutyHours/dh_dutyhoursCommonPR07012007.pdf
 
Trivedi MH, Rush AJ, Gaynes BN, Stewart JW, Wisniewski SR, Warden D, Ritz L, Luther JF, Stegman D, Deveaugh-Geiss J, Howland R: Maximizing the adequacy of medication treatment in controlled trials and clinical practice: STAR*D measurement-based care.  Neuropsychopharmacology 2007; 32:2479–2489
 
Weiss AP, Guidi J, Fava M: Closing the efficacy-effectiveness gap: translating both the what and the how from randomized controlled trials to clinical practice.  J Clin Psychiatry 2009; 70:446–449
 
Institute of Medicine: Improving the Quality of Health Care for Mental and Substance-Use Conditions:  Quality Chasm Series .  Washington, DC,  National Academy Press, 2006
 
Bauer MS: A review of qualitative studies of adherence to mental health clinical practice guidelines.  Harv Rev Psychiatry 2002; 10:138–153
 
Compton MT, Rudisch BE, Craw J, Thompson T, Owens DA: Predictors of missed first appointments at community mental health centers after psychiatric hospitalization.  Psychiatr Serv 2006; 57:531–537
 
Larkin GL, Smith RP, Beautrais AL: Trends in US emergency department visits for suicide attempts, 1992–2001.  Crisis 2008; 29:73–80
 
Suite DH, La Bril R, Primm A, Harrison-Ross P: Beyond misdiagnosis, misunderstanding and mistrust: relevance of the historical perspective in the medical and mental health treatment of people of color.  J Natl Med Assoc 2007; 99:879–885
 
Lawson WB: Issues in Pharmacotherapy for African Americans, in Ethnicity and Psychopharmacology. Edited by Ruiz P (Review of Psychiatry Series, vol 19, no. 4. Oldham JO and Riba MB, Series Eds.).  Washington, DC,  American Psychiatric Press, 2000, pp 37–47
 
Strakowski SM, Shelton RC, Kolbrener ML: The effects of race and comorbidity on clinical diagnosis in patients with psychosis.  J Clin Psychiatry 1993; 54:96–102
 
Baker, FM Bell CC: Issues in the psychiatric treatment of African Americans.  Psychiatry Serv 1999; 50:362–368
 
Bhui K, Stansfeld S, Hull S, Priebe S, Mole F, Feder G: Ethnic variations in pathways to and use of specialist mental health services in the UK. Systematic review.  Br J Psychiatry 2003; 182:105–116
 
Rawal PH, Lyons JS, MacIntyre JC 2nd, Hunter JC: Regional variation and clinical indicators of antipsychotic use in residential treatment: a four-state comparison.  J Behav Health Serv Res 2004; 31:178–188
 
Olfson M, Blanco C, Liu L, Moreno C, Laje G: National trends in the outpatient treatment of children and adolescents with antipsychotic drugs.  Arch Gen Psychiatry 2006; 63:679–685
 
National Institute of Mental Health:  Statistics . 2009. http://www.nimh.nih.gov/health/topics/statistics/index.shtml
 
Insel TR: Assessing the economic costs of serious mental illness.  Am J Psychiatry 2008; 165:663–665
 
Stewart WF, Ricci, JA, Chee E, Hahn SR, Morganstein D. Cost of lost productive work time among US workers with depression.  JAMA 2003; 289:3135–3144
 
Kessler RC, Demler O, Frank RG, Olfson M, Pincus HA, Walters EE, Wang P, Wells KB, Zaslavsky AM: Prevalence and treatment of mental disorders, 1990 to 2003.  N Engl J Med 2005; 352:2515–2523
 
Substance Abuse and Mental Health Services Administration: Results from the 2005 National Survey on Drug Use and Health, vol I.  Summary of National Findings . 2005. http://www.oas.samhsa.gov/nsduh/2k5nsduh/2k5results.htm#8.1
 
Substance Abuse and Mental Health Services Administration: Results from the 2009 National Survey on Drug Use and Health: vol I.  Summary of National Findings . 2010. http://oas.samhsa.gov/NSDUH/2k9NSDUH/2k9Results.htm
 
Weaver MR, Conover CJ, Proescholdbell RJ, Arno PS, Ang A, Ettner SL, Cost Subcommittee of the HIV/AIDS Treatment Adherence, Health Outcomes, and Cost Study Group: Utilization of mental health and substance abuse care for people living with HIV/AIDS, chronic mental illness, and substance abuse disorders.  J Acquir Immune Defic Syndr 2008; 47:449–458
 
Jaycox LH, Morral AR, Juvonen J: Mental heath and medical problems and service use among adolescent substance users.  J Am Acad Child Adolesc Psychiatry 2003; 42:701–709
 
Sareen J, Jagdeo A, Cox BJ, Clara I, ten Have M, Belik SL, de Graaf R, Stein MB: Perceived barriers to mental health service utilization in the United States, Ontario, and the Netherlands.  Psychiatr Serv 2007; 58:357–364
 
Keyes KM, Hatzenbuehler ML, Alberti P, Narrow WE, Grant BF, Hasin DS: Service utilization differences for axis I psychiatric and substance use disorders between white and black adults.  Psychiatr Serv 2008; 59:893–901
 
Bates DW, Shore MF, Gibson R, Bosk C: Patient safety forum: examining the evidence: do we know if psychiatric inpatients are being harmed by errors? What level of confidence should we have in data on the absence or presence of unintended harm?  Psychiatr Serv 2003; 54:1599–1603
 
Nath SB, Marcus SC: Medical errors in psychiatry.  Harv Rev Psychiatry 2006; 14:204–211
 
Rothschild JM, Mann K, Keohane CA, Williams DH, Foskett C, Rosen SL, Flaherty L, Chu JA, Bates DW: Medication safety in a psychiatric hospital.  Gen Hosp Psychiatry 2007; 29:156–162
 
Cullen SW, Nath SB, Marcus SC: Toward understanding errors in inpatient psychiatry: a qualitative inquiry.  Psychiatr Q 2010; 81:197–205
 
Jayaram G: Measuring adverse events in psychiatry.  Psychiatry (Edgmont) 2008; 5:17–19
 
Grasso BC, Rothschild JM, Genest R, Bates DW: What do we know about medication errors in inpatient psychiatry?  Jt Comm J Qual Saf 2003; 29:391–400
 
Leape LL: Error in medicine.  JAMA . 1994;272:1851–1857
 
Leape LL, Berwick D: Five years after to err is human: what have we learned?  JAMA 2005; 293:2384–2390
 
Smith GM, Davis RH, Bixler EO, Lin HM, Altenor A, Altenor RJ, Hardentstine BD, Kopchick GA: Pennsylvania State Hospital system's seclusion and restraint reduction program.  Psychiatr Serv 2005; 56:1115–1122
 
Wagner EH: Chronic disease management: what will it take to improve care for chronic illness?  Eff Clin Pract 1998; 1:2–4
 
Harding KJ, Rush AJ, Arbuckle M, Trivedi MH, Pincus HA: Measurement-based care in psychiatric practice: a policy framework for implementation.  J Clin Psychiatry (in press)
 
Ramirez Basco M, Bostic JQ, Davies D, Rush AJ, Witte B, Hendrickse W, Barnett V: Methods to improve diagnostic accuracy in a community mental health setting.  Am J Psychiatry 2000; 157:1599–1605
 
Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, Norquist G, Howland RH, Lebowitz B, McGrath PJ, Shores-Wilson K, Biggs MM, Balasubramani GK, Fava M, STAR*D Study Team: Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice.  Am J Psychiatry 2006; 163:28–40
 
Trivedi MH, Rush AJ, Crismon ML, Kashner TM, Toprac MG, Carmody TJ, Key T, Biggs MM, Shores-Wilson K, Witte B, Suppes T, Miller AL, Altshuler KZ, Shon SP: Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project.  Arch Gen Psychiatry 2004; 61:669–680
 
Smith TE, Sederer LI: A new kind of homelessness for individuals with serious mental illness? The need for a “mental health home.”  Psychiatr Serv 2009; 60:528–533
 
Bodenheimer T, Wagner EH, Grumbach K: Improving primary care for patients with chronic illness.  JAMA 2002; 288:1775–1779
 
Bodenheimer T, Wagner EH, Grumbach K: Improving primary care for patients with chronic illness: the chronic care model, part 2.  JAMA 2002; 288:1909–1914
 
Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A: Improving chronic illness care: translating evidence into action.  Health Aff (Millwood) 2001; 20:64–78
 
American College of Physicians: The Advanced Medical Home: A Patient-Centered.  Physician-Guided Model of Health Care .  Philadelphia,  American College of Physicians, 2006
 
Smith TE, Sederer LI: A new kind of homelessness for individuals with serious mental illness? The need for a “mental health home.”  Psychiatr Serv 2009; 60:528–533
 
Deegan PE, Drake RE: Shared decision making and medication management in the recovery process.  Psychiatr Serv 2006; 57:1636–1639
 
Agency for Health Care Policy and Research: Depression in Primary Care, vols. 1 and 2: Detection, Diagnosis and Treatment of Major Depression.  Clinical Practice Guidelines .  Rockville, MD,  Agency for Health Care Policy and Research, 1993
 
Bodenheimer T, Laing BY: The teamlet model of primary care.  Ann Fam Med 2007; 5:457–461
 
Katon WJ, Lin EH, Von Korff M, Ciechanowski P, Ludman EJ, Young B, Peterson D, Rutter CM, McGregor M, McCulloch D: Collaborative care for patients with depression and chronic illnesses.  N Engl J Med 2010;363:2611–2620
 
Sherbourne CD, Hays RD, Ordway L, DiMatteo MR, Kravitz RL: Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study.  J Behav Med 1992; 15:447–468
 
Oslin DW, Ross J, Sayers S, Murphy J, Kane V, Katz IR: Screening, assessment, and management of depression in VA primary care clinics. The Behavioral Health Laboratory.  J Gen Intern Med 2006; 21:46–50
 
Ortiz DD: Using a simple patient registry to improve your chronic disease care.  Fam Pract Manag 2006; 13:47–48, 51–52
 
Ting HH, Kaveh GS, Montori VM, Bradley EH: Quality improvement: science and action.  Circulation 2009; 119:1962–1974
 
Deming WE:  Out of the Crisis .  Cambridge, MA,  Center for Advanced Engineering Study, 1986
 
Blumenthal D, Kilo CM: A report card on continuous quality improvement.  Milbank Q 1998; 76:625–648
 
Speroff T, O'Connor GT: Study designs for PDSA quality improvement research.  Qual Manag Health Care 2004; 13:17–32
 
American Psychiatric Association:  Practice Guidelines for the Treatment of Psychiatric Disorders .  Arlington, VA,  American Psychiatric Association, 2006
 
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ: Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.  Hypertension 2003; 42:1206–1252
 
Towner S: Chronic disease management at Intermountain Healthcare.  Front Health Serv Manag 2008; 25(2):3–14
 
Blumenthal D: Stimulating the adoption of health information technology.  N Engl J Med 2009; 360:1477–1479
 
U.S. Department of Health and Human Services:  News Release . http://www.hhs.gov/news/press/2011pres/01/20110113a.html
 
Pincus HA, Spaeth-Rublee B, Watkins KE: The case for measuring quality in mental health and substance abuse care.  Health Aff 2011; 30:730–6
 
Institute of Medicine: Provision of Mental Health Counseling Services under TRICARE.  Washington, DC,  National Academy Press, 2010
 
Pincus HA: From PORT to policy to patient outcomes: crossing the quality chasm.  Schizophr Bull 2010; 36:109–111
 
Rosenthal MB, Frank RG, Li Z, Epstein AM: Early experience with pay-for-performance: from concept to practice.  JAMA 2005; 294:1788–1793
 
Ginsburg PB: Rapidly evolving physician-payment policy—more than the SGR.  N Engl J Med 2011; 364:172–176
 
Rosenthal MB, Landon BE, Normand SL, Frank RG, Epstein AM: Pay for performance in commercial HMOs.  N Engl J Med 2006; 355:1895–1902
 
Bremer RW, Scholle SH, Keyser D, Houtsinger JVK, Pincus HA: Pay for performance in behavioral health.  Psychiatr Serv 2008; 59:1419–1429
 
Institute for Clinical System Improvement: Depression Improvement Across Minnesota, Offering a New Direction,  DIAMOND Project . http://www.icsi.org/health_care_redesign_/diamond_35953/diamond_35991.html
 
Smith D, York N: Quality incentives: the case of U.K. general practitioners.  Health Aff (Millwood) 2004; 23:112–118
 
Lester H, Schmittdiel J, Selby J, Fireman B, Campbell S, Lee J, Whippy A, Madvig P: The impact of removing financial incentives from clinical quality indicators: longitudinal analysis of four Kaiser Permanente indicators.  BMJ 2010; 340:c1898
 
Hamilton AB, Cohen AN, Young AS: Organizational readiness in specialty mental health care.  J Gen Intern Med 2010; 25(suppl 1):27–31
 
Jha AK, Epstein AM: Hospital Performance Improvement: Are Things Getting Better?  The Commonwealth Fund ,  New York, 2007
 
Berwick DM, James B, Coye MJ: Connections between quality measurement and improvement.  Med Care 2003; 41(suppl):130–138
 
Institute for Healthcare Improvement: www.IHI.org/ihi/about
 
NIATx: Removing Barriers to Treatment & Recovery. http://www.niatx.net/Home/Home.aspx
 
Oldham JM, Golden WE, Rosof BM: Quality improvement in psychiatry: why measures matter.  J Psychiatr Pract 2008; 14(suppl 2):8–17
 
Institute of Medicine: Initial National Priorities for Comparative Effectiveness Research.  Washington, DC,  National Academy Press, 2011
 
Accreditation Council for Graduate Medical Education:  Outcome Project . http://www.acgme.org/outcome/about/faq.asp#a8
 
Wallack L, Lawrence R: Talking about public health: developing America's “second language.”  Am J Public Health 2005; 95:567–570
 
Swensen SJ, Meyer GS, Nelson EC, Hunt GC Jr, Pryor DB, Weissberg JI, Kaplan GS, Daley J, Yates GR, Chassin MR, James BC, Berwick DM: Cottage industry to postindustrial care—the revolution in health care delivery.  N Engl J Med 2010; 362:e12
 
References Container

Figure 1. The 10 Rules for Patient/consumer Expectations of Their Health Care System

[Adapted from Institute of Medicine: To Err Is Human: Building a Safer Health System. Washington DC, National Academy Press, 2000; and Berwick DM: A user's manual for the IOM's ‘Quality Chasm’ report. Health Aff (Millwood) 2002; 21(3):80–90.]

Figure 2. 

The Chronic Care Model

Figure 3. Preparing for the Future in Mental Health

(Reproduced with permission from Pincus HA: Crossing the quality chasm. Schizophr Bull 2010; 36:109–111. Copyright © The Author 2009. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.)

+

References

Institute of Medicine: To Err Is Human: Building a Safer Health System.  Washington DC,  National Academy Press, 2000
 
Institute of Medicine: Crossing the Quality Chasm: A New Health System for the 21st Century.  Washington, DC,  National Academy Press, 2001
 
Davis K, Schoen C, Stremikis K: Mirror Mirror on the Wall: How the Performance of the US Health Care System Compares Internationally. 2010 Update.  New York,  The Commonwealth Fund, 2010
 
World Health Organization: The World Health Report 2000—Health Systems: Improving Performance. http://www.who.int/whr/2000/en/
 
World Health Organization: World Health Organization Assesses the World's Health Systems. 2000. http://www.who.int/whr/2000/media_centre/press_release/en/index.html
 
National Committee for Quality Assurance: The state of health care quality. 2010. http://www.ncqa.org/tabid/836/Default.aspx
 
McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA: The quality of health care delivered to adults in the United States.  N Engl J Med 2003; 348:2635–2645
 
Asch SM, Kerr EA, Keesey J, Adams JL, Setodji CM, Malik S, McGlynn EA: Who is at greatest risk for receiving poor-quality health care?  N Engl J Med 2006; 354:1147–1156
 
Wennberg JE, Fisher, ES, Goodman DC, Skinner JS: Tracking the Care of Patients with Severe Chronic Illness. The Dartmouth Atlas of Health Care 2008.  Executive Summary .  Dartmouth, NH,  The Dartmouth Institute for Health Policy and Clinical Practice, 2008
 
Herbstman BJ, Pincus HA: Measuring mental healthcare quality in the United States: a review of initiatives.  Curr Opin Psychiatry 2009; 22:623–630
 
Accreditation Council for Graduate Medical Education: Common Program Requirements. Effective July 1, 2007. http://www.acgme.org/acWebsite/dutyHours/dh_dutyhoursCommonPR07012007.pdf
 
Trivedi MH, Rush AJ, Gaynes BN, Stewart JW, Wisniewski SR, Warden D, Ritz L, Luther JF, Stegman D, Deveaugh-Geiss J, Howland R: Maximizing the adequacy of medication treatment in controlled trials and clinical practice: STAR*D measurement-based care.  Neuropsychopharmacology 2007; 32:2479–2489
 
Weiss AP, Guidi J, Fava M: Closing the efficacy-effectiveness gap: translating both the what and the how from randomized controlled trials to clinical practice.  J Clin Psychiatry 2009; 70:446–449
 
Institute of Medicine: Improving the Quality of Health Care for Mental and Substance-Use Conditions:  Quality Chasm Series .  Washington, DC,  National Academy Press, 2006
 
Bauer MS: A review of qualitative studies of adherence to mental health clinical practice guidelines.  Harv Rev Psychiatry 2002; 10:138–153
 
Compton MT, Rudisch BE, Craw J, Thompson T, Owens DA: Predictors of missed first appointments at community mental health centers after psychiatric hospitalization.  Psychiatr Serv 2006; 57:531–537
 
Larkin GL, Smith RP, Beautrais AL: Trends in US emergency department visits for suicide attempts, 1992–2001.  Crisis 2008; 29:73–80
 
Suite DH, La Bril R, Primm A, Harrison-Ross P: Beyond misdiagnosis, misunderstanding and mistrust: relevance of the historical perspective in the medical and mental health treatment of people of color.  J Natl Med Assoc 2007; 99:879–885
 
Lawson WB: Issues in Pharmacotherapy for African Americans, in Ethnicity and Psychopharmacology. Edited by Ruiz P (Review of Psychiatry Series, vol 19, no. 4. Oldham JO and Riba MB, Series Eds.).  Washington, DC,  American Psychiatric Press, 2000, pp 37–47
 
Strakowski SM, Shelton RC, Kolbrener ML: The effects of race and comorbidity on clinical diagnosis in patients with psychosis.  J Clin Psychiatry 1993; 54:96–102
 
Baker, FM Bell CC: Issues in the psychiatric treatment of African Americans.  Psychiatry Serv 1999; 50:362–368
 
Bhui K, Stansfeld S, Hull S, Priebe S, Mole F, Feder G: Ethnic variations in pathways to and use of specialist mental health services in the UK. Systematic review.  Br J Psychiatry 2003; 182:105–116
 
Rawal PH, Lyons JS, MacIntyre JC 2nd, Hunter JC: Regional variation and clinical indicators of antipsychotic use in residential treatment: a four-state comparison.  J Behav Health Serv Res 2004; 31:178–188
 
Olfson M, Blanco C, Liu L, Moreno C, Laje G: National trends in the outpatient treatment of children and adolescents with antipsychotic drugs.  Arch Gen Psychiatry 2006; 63:679–685
 
National Institute of Mental Health:  Statistics . 2009. http://www.nimh.nih.gov/health/topics/statistics/index.shtml
 
Insel TR: Assessing the economic costs of serious mental illness.  Am J Psychiatry 2008; 165:663–665
 
Stewart WF, Ricci, JA, Chee E, Hahn SR, Morganstein D. Cost of lost productive work time among US workers with depression.  JAMA 2003; 289:3135–3144
 
Kessler RC, Demler O, Frank RG, Olfson M, Pincus HA, Walters EE, Wang P, Wells KB, Zaslavsky AM: Prevalence and treatment of mental disorders, 1990 to 2003.  N Engl J Med 2005; 352:2515–2523
 
Substance Abuse and Mental Health Services Administration: Results from the 2005 National Survey on Drug Use and Health, vol I.  Summary of National Findings . 2005. http://www.oas.samhsa.gov/nsduh/2k5nsduh/2k5results.htm#8.1
 
Substance Abuse and Mental Health Services Administration: Results from the 2009 National Survey on Drug Use and Health: vol I.  Summary of National Findings . 2010. http://oas.samhsa.gov/NSDUH/2k9NSDUH/2k9Results.htm
 
Weaver MR, Conover CJ, Proescholdbell RJ, Arno PS, Ang A, Ettner SL, Cost Subcommittee of the HIV/AIDS Treatment Adherence, Health Outcomes, and Cost Study Group: Utilization of mental health and substance abuse care for people living with HIV/AIDS, chronic mental illness, and substance abuse disorders.  J Acquir Immune Defic Syndr 2008; 47:449–458
 
Jaycox LH, Morral AR, Juvonen J: Mental heath and medical problems and service use among adolescent substance users.  J Am Acad Child Adolesc Psychiatry 2003; 42:701–709
 
Sareen J, Jagdeo A, Cox BJ, Clara I, ten Have M, Belik SL, de Graaf R, Stein MB: Perceived barriers to mental health service utilization in the United States, Ontario, and the Netherlands.  Psychiatr Serv 2007; 58:357–364
 
Keyes KM, Hatzenbuehler ML, Alberti P, Narrow WE, Grant BF, Hasin DS: Service utilization differences for axis I psychiatric and substance use disorders between white and black adults.  Psychiatr Serv 2008; 59:893–901
 
Bates DW, Shore MF, Gibson R, Bosk C: Patient safety forum: examining the evidence: do we know if psychiatric inpatients are being harmed by errors? What level of confidence should we have in data on the absence or presence of unintended harm?  Psychiatr Serv 2003; 54:1599–1603
 
Nath SB, Marcus SC: Medical errors in psychiatry.  Harv Rev Psychiatry 2006; 14:204–211
 
Rothschild JM, Mann K, Keohane CA, Williams DH, Foskett C, Rosen SL, Flaherty L, Chu JA, Bates DW: Medication safety in a psychiatric hospital.  Gen Hosp Psychiatry 2007; 29:156–162
 
Cullen SW, Nath SB, Marcus SC: Toward understanding errors in inpatient psychiatry: a qualitative inquiry.  Psychiatr Q 2010; 81:197–205
 
Jayaram G: Measuring adverse events in psychiatry.  Psychiatry (Edgmont) 2008; 5:17–19
 
Grasso BC, Rothschild JM, Genest R, Bates DW: What do we know about medication errors in inpatient psychiatry?  Jt Comm J Qual Saf 2003; 29:391–400
 
Leape LL: Error in medicine.  JAMA . 1994;272:1851–1857
 
Leape LL, Berwick D: Five years after to err is human: what have we learned?  JAMA 2005; 293:2384–2390
 
Smith GM, Davis RH, Bixler EO, Lin HM, Altenor A, Altenor RJ, Hardentstine BD, Kopchick GA: Pennsylvania State Hospital system's seclusion and restraint reduction program.  Psychiatr Serv 2005; 56:1115–1122
 
Wagner EH: Chronic disease management: what will it take to improve care for chronic illness?  Eff Clin Pract 1998; 1:2–4
 
Harding KJ, Rush AJ, Arbuckle M, Trivedi MH, Pincus HA: Measurement-based care in psychiatric practice: a policy framework for implementation.  J Clin Psychiatry (in press)
 
Ramirez Basco M, Bostic JQ, Davies D, Rush AJ, Witte B, Hendrickse W, Barnett V: Methods to improve diagnostic accuracy in a community mental health setting.  Am J Psychiatry 2000; 157:1599–1605
 
Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, Norquist G, Howland RH, Lebowitz B, McGrath PJ, Shores-Wilson K, Biggs MM, Balasubramani GK, Fava M, STAR*D Study Team: Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice.  Am J Psychiatry 2006; 163:28–40
 
Trivedi MH, Rush AJ, Crismon ML, Kashner TM, Toprac MG, Carmody TJ, Key T, Biggs MM, Shores-Wilson K, Witte B, Suppes T, Miller AL, Altshuler KZ, Shon SP: Clinical results for patients with major depressive disorder in the Texas Medication Algorithm Project.  Arch Gen Psychiatry 2004; 61:669–680
 
Smith TE, Sederer LI: A new kind of homelessness for individuals with serious mental illness? The need for a “mental health home.”  Psychiatr Serv 2009; 60:528–533
 
Bodenheimer T, Wagner EH, Grumbach K: Improving primary care for patients with chronic illness.  JAMA 2002; 288:1775–1779
 
Bodenheimer T, Wagner EH, Grumbach K: Improving primary care for patients with chronic illness: the chronic care model, part 2.  JAMA 2002; 288:1909–1914
 
Wagner EH, Austin BT, Davis C, Hindmarsh M, Schaefer J, Bonomi A: Improving chronic illness care: translating evidence into action.  Health Aff (Millwood) 2001; 20:64–78
 
American College of Physicians: The Advanced Medical Home: A Patient-Centered.  Physician-Guided Model of Health Care .  Philadelphia,  American College of Physicians, 2006
 
Smith TE, Sederer LI: A new kind of homelessness for individuals with serious mental illness? The need for a “mental health home.”  Psychiatr Serv 2009; 60:528–533
 
Deegan PE, Drake RE: Shared decision making and medication management in the recovery process.  Psychiatr Serv 2006; 57:1636–1639
 
Agency for Health Care Policy and Research: Depression in Primary Care, vols. 1 and 2: Detection, Diagnosis and Treatment of Major Depression.  Clinical Practice Guidelines .  Rockville, MD,  Agency for Health Care Policy and Research, 1993
 
Bodenheimer T, Laing BY: The teamlet model of primary care.  Ann Fam Med 2007; 5:457–461
 
Katon WJ, Lin EH, Von Korff M, Ciechanowski P, Ludman EJ, Young B, Peterson D, Rutter CM, McGregor M, McCulloch D: Collaborative care for patients with depression and chronic illnesses.  N Engl J Med 2010;363:2611–2620
 
Sherbourne CD, Hays RD, Ordway L, DiMatteo MR, Kravitz RL: Antecedents of adherence to medical recommendations: results from the Medical Outcomes Study.  J Behav Med 1992; 15:447–468
 
Oslin DW, Ross J, Sayers S, Murphy J, Kane V, Katz IR: Screening, assessment, and management of depression in VA primary care clinics. The Behavioral Health Laboratory.  J Gen Intern Med 2006; 21:46–50
 
Ortiz DD: Using a simple patient registry to improve your chronic disease care.  Fam Pract Manag 2006; 13:47–48, 51–52
 
Ting HH, Kaveh GS, Montori VM, Bradley EH: Quality improvement: science and action.  Circulation 2009; 119:1962–1974
 
Deming WE:  Out of the Crisis .  Cambridge, MA,  Center for Advanced Engineering Study, 1986
 
Blumenthal D, Kilo CM: A report card on continuous quality improvement.  Milbank Q 1998; 76:625–648
 
Speroff T, O'Connor GT: Study designs for PDSA quality improvement research.  Qual Manag Health Care 2004; 13:17–32
 
American Psychiatric Association:  Practice Guidelines for the Treatment of Psychiatric Disorders .  Arlington, VA,  American Psychiatric Association, 2006
 
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ: Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.  Hypertension 2003; 42:1206–1252
 
Towner S: Chronic disease management at Intermountain Healthcare.  Front Health Serv Manag 2008; 25(2):3–14
 
Blumenthal D: Stimulating the adoption of health information technology.  N Engl J Med 2009; 360:1477–1479
 
U.S. Department of Health and Human Services:  News Release . http://www.hhs.gov/news/press/2011pres/01/20110113a.html
 
Pincus HA, Spaeth-Rublee B, Watkins KE: The case for measuring quality in mental health and substance abuse care.  Health Aff 2011; 30:730–6
 
Institute of Medicine: Provision of Mental Health Counseling Services under TRICARE.  Washington, DC,  National Academy Press, 2010
 
Pincus HA: From PORT to policy to patient outcomes: crossing the quality chasm.  Schizophr Bull 2010; 36:109–111
 
Rosenthal MB, Frank RG, Li Z, Epstein AM: Early experience with pay-for-performance: from concept to practice.  JAMA 2005; 294:1788–1793
 
Ginsburg PB: Rapidly evolving physician-payment policy—more than the SGR.  N Engl J Med 2011; 364:172–176
 
Rosenthal MB, Landon BE, Normand SL, Frank RG, Epstein AM: Pay for performance in commercial HMOs.  N Engl J Med 2006; 355:1895–1902
 
Bremer RW, Scholle SH, Keyser D, Houtsinger JVK, Pincus HA: Pay for performance in behavioral health.  Psychiatr Serv 2008; 59:1419–1429
 
Institute for Clinical System Improvement: Depression Improvement Across Minnesota, Offering a New Direction,  DIAMOND Project . http://www.icsi.org/health_care_redesign_/diamond_35953/diamond_35991.html
 
Smith D, York N: Quality incentives: the case of U.K. general practitioners.  Health Aff (Millwood) 2004; 23:112–118
 
Lester H, Schmittdiel J, Selby J, Fireman B, Campbell S, Lee J, Whippy A, Madvig P: The impact of removing financial incentives from clinical quality indicators: longitudinal analysis of four Kaiser Permanente indicators.  BMJ 2010; 340:c1898
 
Hamilton AB, Cohen AN, Young AS: Organizational readiness in specialty mental health care.  J Gen Intern Med 2010; 25(suppl 1):27–31
 
Jha AK, Epstein AM: Hospital Performance Improvement: Are Things Getting Better?  The Commonwealth Fund ,  New York, 2007
 
Berwick DM, James B, Coye MJ: Connections between quality measurement and improvement.  Med Care 2003; 41(suppl):130–138
 
Institute for Healthcare Improvement: www.IHI.org/ihi/about
 
NIATx: Removing Barriers to Treatment & Recovery. http://www.niatx.net/Home/Home.aspx
 
Oldham JM, Golden WE, Rosof BM: Quality improvement in psychiatry: why measures matter.  J Psychiatr Pract 2008; 14(suppl 2):8–17
 
Institute of Medicine: Initial National Priorities for Comparative Effectiveness Research.  Washington, DC,  National Academy Press, 2011
 
Accreditation Council for Graduate Medical Education:  Outcome Project . http://www.acgme.org/outcome/about/faq.asp#a8
 
Wallack L, Lawrence R: Talking about public health: developing America's “second language.”  Am J Public Health 2005; 95:567–570
 
Swensen SJ, Meyer GS, Nelson EC, Hunt GC Jr, Pryor DB, Weissberg JI, Kaplan GS, Daley J, Yates GR, Chassin MR, James BC, Berwick DM: Cottage industry to postindustrial care—the revolution in health care delivery.  N Engl J Med 2010; 362:e12
 
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CME Activity

Add a subscription to complete this activity and earn CME credit.
Sample questions:
1.
Which of the following is an example of the "new rules" for patient/consumer expectations of their health care system as described by the Institute of Medicine's ‘Quality Chasm’ series?

See Harding: Figure 1: The 10 rules for patient/consumer expectations of their health care system, p 156
2.
What is the estimated lag in the translation of biomedical research into actual clinical practice, also known as the "bench to bedside" delay?

See Harding: Why Quality Matters, p 153
3.
Understanding and improving the current state of health care quality in clinicians' own practices falls primarily under which of the general competencies?

See Harding: Why Quality Matters, p 154
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