Striving to improve patient care is integral to the practice of medicine. Doing so in a systematic way, however, is a fairly recent phenomenon.
Momentum for such efforts was building by the late 1990s, and the Centers for Medicare and Medicaid Services (CMS) has required hospitals to maintain quality assessment and performance improvement programs as a condition of participation since 2003.1 In 2008, the Institute for Healthcare Improvement proposed the Triple Aim of health care in the United States: (1) improved health for populations, (2) lower per capita cost, and (3) better patient experience.2 CMS officially adopted this goal by 2010, and the Triple Aim strongly informed the design of President Barack Obama's Patient Protection and Affordable Care Act.3
Progress toward the Triple Aim is thought to require reform of both health care financing and delivery. Whether in the form of accountable care organizations or advanced alternative payment models, the goal is to incentivize health care organizations to improve value by “standardizing processes, enhancing efficiency of care delivery systems, and optimizing capacity across care delivery systems.”4
During much of the same time period, interest in new ways to deliver psychiatric care has grown steadily. PubMed citations for collaborative care increased from just 15 in the year 2000 to 110 in 2010 to 231 by 2016. Integrated and collaborative care programs have been implemented at scale in a variety of settings, including the states of Washington (Mental Health Integration Program) and Minnesota (Depression Improvement Across Minnesota, Offering a New Direction), as well as the US Army (Re-Engineering Systems of Primary Care Treatment in the Military) and Veterans Affairs (VA) Health System. Although involving a range of models, such programs are united by a goal of bringing behavioral health and primary care closer together to improve patient care.
These two movements—Quality Improvement (QI) and Integrated Collaborative Care (ICC)—are closely aligned and overlap in many ways. After a brief overview of the history of QI, this article discusses three key aspects of this interaction.
What Is Quality Improvement?
QI is the continuous and systematic attempt to improve the performance of a system in measurable ways. The fundamental concepts of QI emerged organically from manufacturing and the military in the early 20th century, as managers realized the usefulness of standardizing work and inspecting for defects. Pioneers such as Walter Shewhart developed statistical process control methods to track the outputs of a system,5 such as an individual factory, and identified problematic variation in quality.
After World War II, Japan's industrial economy underwent a “quality revolution,” incorporating the ideas of experts such W. Edwards Deming and his System of Profound Knowledge.6 Rather than focusing on defects in a system's output, Deming's philosophy emphasized continuous improvement of the entire organization and work processes.
During the subsequent decades, models like Total Quality Management and Lean Manufacturing migrated out of Japan and took root in the US and Europe. By the end of the 20th century, QI fundamentals such as Plan-Do-Study-Act (PDSA) cycles, minimizing variation in processes, and analysis of root cause were standard practice throughout manufacturing, retail supply chains, and other industries.
The US health care system did not embrace QI until the late 1990s, spurred on by the Institute of Medicine's publication of “To Err is Human”7 in 1999 and “Crossing the Quality Chasm”8 in 2001. Although still lagging behind other sectors of the economy, “more organizations than ever before are actively engaged in a wide variety of improvement efforts.”9
Models of Quality Improvement
A number of versions of QI exist, each emphasizing different aspects of shared core principles (Table 1). The Institute for Healthcare Improvement advocates their own Model for Improvement, a synthesis and simplification of many QI concepts. The model approaches problems with three basic questions in mind: (1) What are we trying to accomplish? (2) How will we know that a change is an improvement? (3) What change can we make that will result in improvement? Data-based PDSA cycles then drive successive iterations of improvement.10
Suggested Uses of Quality Improvement in Behavioral Health
“Lean” thinking is another branch of QI and emphasizes simultaneously improving quality and lowering costs by eliminating waste, which is defined as any activity that does not add value from the patient's perspective. This includes common issues such as wait times, unnecessary movement of patients or staff, and defects. Other tenets of Lean include reducing inventory and batches within a process, with the goal of “just-in-time” production.11
Six Sigma is a highly quantitative, data-oriented approach to QI. It focuses on eliminating defects in high-volume processes. Six Sigma advocates the use of DMAIC cycles (Define, Measure, Analyze, Improve and Control), which are conceptually similar to the more common PDSA cycles. In health care, Six Sigma is most applicable in areas such as the laboratory and pharmacy.12,13
Developed to address the unique challenges of implementing effective treatments in health care, Evidence-Based Quality Improvement (EBQI) is an approach “whose goal is translation of research on care delivery models into routine practice.”14 EBQI advocates the use of research-clinical partnerships to implement validated care models and clinical guidelines.
Integrated and Collaborative Care Programs Are an Application of QI Principles
Integrating behavioral health and primary care can be viewed as a QI initiative. The two movements share many basic tenets. For instance, the principle of patient-centered team care involves the idea of the patient defining value as well as the idea of relying on front-line workers, not management, to generate improvement ideas.15 There is also a shared emphasis on the use of data to drive changes in day-to-day workflows.
More specifically, the care-delivery innovations present in such models represent Lean ideas in action. ICC models differ logistically from standard practice in important ways: patients are seen in their primary care office, referrals are tightly coupled or instantaneous as “warm handoffs,” and psychiatrists see only a minority of complex or refractory cases. From a Lean perspective, these changes represent the elimination of major waste: unnecessary patient movement to another clinic, waiting time of weeks or more for intake appointments, and the “over-processing” of unnecessarily intense levels of service (Table 2).
Types and Examples of Waste in Behavioral Health
This connection was made explicit by the authors of a 2008 study, who implemented an integrated care program as part of a QI effort.16 Prior to intervention, there were “long delays for routine mental health consultation and referral” leading to “significant patient attrition and a lost window for effective treatment.”16 The authors sought to define value from the patient's perspective, holding a focus group and finding that “ease of access trumped all other issues.”16 Adoption of a walk-in model, with the explicit intention of improving access, led to dramatic improvement as the “number of referred individuals who actually arrived for an initial evaluation more than doubled in the first 3 months of operation, while the waiting time dropped from weeks to minutes.”16
Integrated and Collaborative Care Programs Can Be Implemented Using QI Tools
Implementation of new clinical programs is challenging, especially when they depart from typical workflows as much as the ICC model. QI tools, especially the EBQI paradigm, can be valuable in managing this change.
EBQI is a set of tools intended to facilitate the implementation of well-established treatment models into clinical practice. Unlike traditional top-down deployments, EBQI encourages management teams to take local context and practice patterns into account, allowing new clinical programs to develop organically.
In the VA Health System, a major initiative sought to establish collaborative care programs at multiple outpatient primary care clinics.17 Clinicians at local sites devised “rapid enlarging PDSA cycles that aimed to test the referral process, safety, process of depression care, and outcomes.”17 Specific workflows were allowed to vary between clinics based on local factors. Compared to controls, those sites using EBQI were more likely to have adequate dosing of antidepressants (65.7% vs 43.4%, P < .01), although no significant differences in symptom outcomes were found.17
Once a ICC program is in place, issues such as maintaining fidelity to the model and sustaining effective provider communication may arise. QI tools such as analysis of root causes can be extremely useful in these situations.
For instance, although the VA has invested heavily in integrated care and Patient-Aligned Care Team models, “the goal of effective, timely communication between PC (primary care) and MH (mental health) remains elusive at local sites.”18 In an innovative attempt to address this problem, the authors used tools such as Fishbone (Ishikawa) diagrams and process flow charts to identify likely communication barriers.18 After validating with focus groups, chart reviews, and provider surveys, they concluded that problem areas included “process, communication tools, provider characteristics, non-VA providers, and culture.”18 The single biggest issue, however, was reliably identifying which providers belonged on a patient-care team.
In another setting, a system of safety net primary care clinics, the implementation of a ICC program was analyzed from a quality improvement perspective.19 Factors that enhanced implementation included co-location of medical and behavioral health services, use of a shared electronic medical record, the presence of physician “champions,” and financial incentives for change. On the other hand, notable barriers included the use of two different computer record systems to track and document clinical information, leading to increased workloads and decreased adherence to recommended care. Staff turnover was another major issue. Finally, financial concerns such as lack of reimbursement for care management led to de-emphasis of these activities.19
Integrated and Collaborative Care Programs Create Opportunities for QI
An active ICC program entails the creation of a robust clinical data set. Electronic medical records and local data registries house clinical data such as symptom changes as well as logistical measures such as visit frequency. This enables practitioners to undertake any number of QI projects, from quantifying clinical response with medication changes, to streamlining referrals, to tracking and decreasing no-show rates.
Ready access to process and outcome data also facilitates the implementation of pay-for-performance programs. In one established ICC system, leadership noted “substantial variation in the quality and outcomes of care” across community health clinics.20 In an effort to “reduce this variation and improve the overall effectiveness” of the system, the administration made 25% of annual funding dependent on clinics meeting a set of key process indicators, such as showing at least two contacts per month for at least half of the caseload, psychiatric consultation for non-improving patients, and tracking of psychotropic medications.20 Once in place, the number of early follow-up visits significantly increased whereas the median time to response or remission decreased from 64 to 25 weeks. The authors concluded that “institution of a quality improvement program with a P4P (pay for performance) incentive substantially improved the quality and outcomes of care.”20
ICC models represent improvements on traditional care in many important ways. Reliable clinical data are obtained to drive treatment decisions, patients are tracked in a standardized and systematic fashion, the level of service is “right-sized” to the clinical needs, care is more convenient for the patients, and each provider is ultimately more productive. These are exactly the sort of changes that QI frameworks would advocate. In addition, QI tools are useful in implementing, maintaining, and further improving on these models of care. More widespread adoption of QI tools will help further drive innovation in psychiatric care delivery.
- Centers for Medicare & Medicaid Services. Hospital conditions of participation: quality assessment & performance improvement final rule (68 FR 3435); published January 24, 2003; effective March 25, 2003. https://www.cms.gov/Regulations-and-Guidance/Legislation/CFCsAndCoPs/Hospitals.html. Accessed June 13, 2017.
- Berwick DM, Nolan TW, Whittington J. The triple aim: care, health, and cost. Health Affairs. 2008;27(3):759–769. doi:. doi:10.1377/hlthaff.27.3.759 [CrossRef]
- American Public Health Association. Major Affordable Care Act delivery and payment reforms. October2013. https://www.apha.org/~/media/files/pdf/topics/aca/delivery_reforms_table_apha_oct2013.ashx. Accessed June 13, 2017.
- Duncan J, Mate K. New payment models drive value. Healthcare Executive. 2016;31(6):64–66.
- Shewhart WA.Economic Control of Quality Manufactured Product. Eastford, CT: Martino Fine Books; 2015 (originally published 1931).
- Nilsson Orsini J, ed. The Essential Deming: Leadership Principles from the Father of Quality. New York, NY: McGraw-Hill Education; 2012.
- Kohn LT, Corrigan J, Donaldson MS. To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press; 2000.
- Committee on Quality Health Care in America, Institute of Medicine. Crossing The Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy Press; 2001.
- Chassin MR, Loeb JL. The ongoing quality improvement journey: next stop, high reliability. Health Aff (Millwood). 2011;30(4):559–568. doi:. doi:10.1377/hlthaff.2011.0076 [CrossRef]
- Langley GJ, Moen RD, Nolan KM, , eds. The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. 2nd ed. San Francisco, CA: Jossey-Bass; 2009:1–12.
- Institute for Healthcare Improvement. Going lean in health care. IHI white paper. Cambridge, MA: Institute for Healthcare Improvement; 2005.
- Buck C. Application of Six Sigma to reduce medical errors. American Society for Quality Quality 55th Annual Congress Proceedings. . https://pdfs.semanticscholar.org/3167/37d28a3a9cabb1e83ede4a65b077f23cb0a8.pdf. Accessed June 13, 2017.
- Chaplin E. Six Sigma and its application to healthcare—the application of Six Sigma strategies to medication administration. American Society for Quality 57th Annual Quality Congress Proceedings. . http://www.asq.org/healthcaresixsigma/pdf/ss_application_to_healthcare.pdf. Accessed June 13, 2017.
- Rubinstein LV, Chaney EF, Ober S, et al. Using evidence-based quality improvement methods for translating depression collaborative care research into practice. Families Systems Health. 2010;28(2):91–113. doi:. doi:10.1037/a0020302 [CrossRef]
- Center AIMSPrinciples of collaborative care. https://aims.uw.edu/collaborative-care/principles-collaborative-care. Accessed May 25, 2017.
- Pomerantz A, Cole BH, Watts BV, Weeks WB. Improving efficiency and access to mental health care: combining integrated care and advanced access. Gen Hosp Psychiatry. 2008;30:546–551. doi:. doi:10.1016/j.genhosppsych.2008.09.004 [CrossRef]
- Chaney EF, Rubenstein LV, Liu CF, et al. Implementing collaborative care for depression treatment in primary care: a cluster randomized evaluation of a quality improvement practice redesign. Implementation Science. 2011;6:121. doi:. doi:10.1186/1748-5908-6-121 [CrossRef]
- Chang ET, Wells KB, Young AS, et al. The anatomy of primary care and mental health clinician communication: a quality improvement case study. J Gen Intern Med. 2014;29(Suppl 2):598–606. doi:. doi:10.1007/s11606-013-2731-7 [CrossRef]
- Price-Haywood EG, Dunn-Lombard D, Harden-Barrios J, Lefante J. Collaborative depression care in a safety net medical home: facilitators and barriers to quality improvement. Popul Health Manag. 2016;19(1):46–55. doi:. doi:10.1089/pop.2015.0016 [CrossRef]
- Unutzer J, Chan YF, Hafer E, et al. , Quality improvement with pay-for-performance incentives in integrated behavioral health care. Am J Public Health. 2012;102(6):e41–45. doi:. doi:10.2105/AJPH.2011.300555 [CrossRef]
Suggested Uses of Quality Improvement in Behavioral Health
|Type of Quality Improvement
|Model for Improvement
||Increase rate of screening for metabolic syndrome
Decrease no-show rate for new evaluations
||Improve on-time starts for appointments
Increase throughput of phone screening/intakes
||Eliminate patient medication errors
Decrease turnaround time in laboratory
|Evidence-Based Quality Improvement
||Launch Integrated and Collaborative Care program
Roll out clinic-wide treatment algorithm
Types and Examples of Waste in Behavioral Health
||Patients “lost to follow-up” or no-shows
||Unnecessary evaluations for straightforward cases
||Long delays for appointments
||Redundant or overly complex documentation
||Patient travelling far from home to specialty clinic
||Leaving patient room to find printer