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Published Online: 27 August 2024

Advancing Measurement-Informed Care in Outpatient Community Behavioral Health

Abstract

Measurement-informed care (MIC), also known as measurement-based care or patient-reported outcomes, for behavioral health conditions has had low uptake in the United States. To advance MIC in the near term, the authors reviewed nationally endorsed behavioral health measures and worked with national experts to recommend a core set of outpatient measures to prioritize for use. The resulting set of measures is for common behavioral and comorbid conditions and is outcomes based, low burden, and suitable for value-based payment. The panel of national experts also recommended developing a consensus on quality-of-life measures and functional measures for use across diagnostic categories of the core set.
Behavioral health clinicians and organizations are urged to use repeated clinical measurements, often called measurement-based care (MBC) or patient-reported outcome measures (PROMs), to improve clinical outcomes and to support system needs by justifying, apportioning, and financing care (1, 2). These practices align with those in chronic disease management in general medicine, in which measures such as hemoglobin A1c (HbA1c) are used to determine diabetes care (3) and blood pressure is used to determine care for hypertension (4). Research on the collaborative care model showing that a single measure (i.e., the Patient Health Questionnaire–9 [PHQ-9]) can inform primary care to enhance effectiveness and accountability in depression care (5) suggests that similar strategies may be effective in community behavioral health. Indeed, routine clinical measurements of behavioral health symptoms and other indicators (e.g., the therapeutic alliance) yield a range of benefits, such as improved client retention, reduced no-show rates, and improved clinical outcomes (6, 7). To realize their potential, however, behavioral health measurement approaches must also reflect the science, ideology, and culture of the field.
Several recent reports (1, 2, 8) direct clinicians and organizations toward a curated set of measures for their emerging measurement needs. Although these proposed lists are helpful, stronger consensus is needed around a small core set of measures that can be broadly implemented and sustained. Priority measures for this core set should be aligned with current population health recommendations for screening (i.e., by the U.S. Preventive Services Task Force [USPSTF]), widely endorsed quality measures (i.e., by the National Committee for Quality Assurance [NCQA] and Healthcare Effectiveness Data and Information Set [HEDIS]), and measures with potential for broad use across the range of behavioral health populations and common comorbid conditions.

A Measurement-Informed Care Approach Aligns Measurement Practices for Community Behavioral Health

We propose that a measurement-informed care (MIC) approach can advance repeated clinical measurement in community behavioral health care. We assert that MIC is not a new construct but represents an evolution of MBC that is more explicit about the role of patient-related factors (i.e., cultural, psychological, and social) in clinical decision making. Like MBC, MIC involves repeated measurement of a small set of psychometrically sound, low-burden patient-reported outcomes or biometric measures. These measures are meaningful across clinical and organizational purposes and are sustainable because of their low burden and benefits to patients, providers, payers, and regulatory agencies. Consistent with seminal descriptions of MBC (5), MIC positions measurement as necessary for treatment decision making but not sufficient for determining care. We propose that the term informed has valuable cultural currency, calling attention to the limits of basing care on measurement in behavioral health. MIC also explicitly recognizes variability in patient reporting and provider administration of measurement tools, which can be influenced by health literacy (9) and equity considerations, including varied perspectives on the meaning, purpose, and utility of treatments. Although some readers may prefer other terminology, such as MBC or PROMs, for the measurement process, the collective clinical and academic consensus of the behavioral health experts who contributed to this effort supports the MIC terminology (10).
We conducted a literature review summarizing the available quality measures endorsed by U.S. national health care organizations between September 2022 and February 2023 (10). We then reviewed and coded them along MIC-relevant dimensions, including diagnosis or disorder, population, psychometric properties, process versus outcome orientation, and specification of standardized assessment tools. Fewer than 25% of the >200 identified measures were patient-reported outcomes. A panel of 12 experts in addiction, administration, clinical care, integrated care, primary care, psychology, psychiatry, quality measurement, research, and social work, identified through the authors’ professional networks, reviewed the coded measure set.
The primary theme that expert panel members raised was the disconnect between regulators’, payers’, and general medical partners’ measurement expectations and the availability of suitable measures for MIC in behavioral health. Although regulators and payers were expecting behavioral health systems and clinicians to engage in MIC, the experts asserted that no widely accepted and agreed-upon measures were available for use. The experts attributed this gap to differences between the organization-endorsed quality measures that payers and regulators mandate or incentivize (e.g., HEDIS- or NCQA-endorsed measures) and measures that indicate clinical change or are important to people providing or receiving care. For example, the HEDIS measure of posthospitalization follow-up within 30 days is a useful systemic measure of care quality, but it says little about how clinicians should direct care for an individual. Similarly, the PHQ-9 instrument is a useful indicator of clinical progress, but annual PHQ-9 reassessments are too infrequent to direct care. Further, depression response and remission measures are aligned with MIC, but their reporting specifications are burdensome to providers and of variable interest to payers. Alignment of all parties on a small set of measures that can be used for improving both individual outcomes and value-based care is necessary to reduce provider burden, enable benchmarking across populations, and sustain MIC. (The online supplement to the Open Forum lists criteria used by the expert panel to select measures.)

MIC in Practice: A Two-Tiered Approach

On the basis of the recommendations of our expert panel, we defined MIC as follows: use of reliable and valid service user–reported outcomes or biometric indicators; use of repeated measurements at clinically meaningful, regular intervals; use of measure scores as one among other sources of information (e.g., service user preferences, social driver needs, culture, quality of life, functional needs and goals, family support, health literacy, and others) for making care decisions to support recovery; and use of the same measures to indicate accountability and efficiency of care. Consistent with these recommendations, we propose a two-tiered MIC set of measures for use with adult (ages 18–65 years) outpatient populations who receive community behavioral health services. Additional research is needed to validate the approach with other populations and settings.

Tier 1: Widely Agreed-Upon and Reimbursable Measures for Prevalent Conditions

Conceptually, tier 1 measures are well validated and widely accepted measures (by clinicians and patients), such as those named in clinical consensus statements. These measures are for conditions that affect the general population to the extent that national advisory bodies (i.e., USPSTF) have identified them for routine screening, follow-up, and treatment. Tier 1 measures are aligned with reporting requirements for Medicaid (e.g., through Medicaid health homes or certified community behavioral health clinics) and are used to indicate quality for accreditation and value-based purchasing purposes (3, 4, 1114). Tier 1 measures have quantitative cutoff points to facilitate population health analysis and indicate clinical progress over time (additional details are provided by Chung et al. [10]).
Our six tier 1 measures include three patient self-report outcome measures (the American Psychological Association’s depression response, anxiety response, and alcohol use disorder outcome measures [12]) and three biometric measures for conditions relevant to adults receiving treatment in community behavioral health settings (comprehensive diabetes care for individuals with serious mental illness, such as HbA1c monitoring [11, 14]; comprehensive cardiovascular care for people with serious mental illness, such as blood pressure control [3, 4]; and diabetes monitoring for individuals with both diabetes and schizophrenia [4]). We also propose modifying some measures to improve their MIC suitability, such as increasing assessment frequencies to better inform clinical decision making, especially during the acute treatment phase. (Tier 1 measures and their proposed modifications are detailed in the online supplement.)

Tier 2: Recovery Concepts and Measures Across Diagnostic Categories

Tier 2 measures were selected for their potential to indicate clinical changes across different diagnostic categories and to reflect the whole-person value that is central to behavioral health care. Additional selection criteria were that measures were available for free, easy to access, and simple to use (10). Ultimately, we identified six tier 2 concepts (i.e., disease self-management, functioning, goal attainment, patient experience of care, quality of life, and recovery) and nine candidate measures (10), for example, the WHODAS 2.0 (World Health Organization Disability Assessment Schedule 2.0). Some concepts have multiple candidate measures. We also recommend improving some candidate measures, such as shortening them, resolving psychometric limitations, creating categorical cutoff points to indicate treatment responses, and increasing the frequency of reassessments to enhance the measures’ relevance for clinical care (see the online supplement).
Unlike for tier 1, the concepts and candidate measures for tier 2 are preliminary and need further support from research in clinical settings and more input from people with lived experience. This context keeps us from presently endorsing one tier 2 measure over another. Consistent with recommendations to the Centers for Medicare and Medicaid Services (15), other agencies and organizations can use tier 2 measures as a foundation for developing measure specifications. Organizations that are currently using tier 2 measures for MIC are encouraged to publish their work in order to demonstrate the utility of these measures and narrow the focus of the field.

Conclusions

MIC has the potential to improve behavioral health measurement uptake, implementation, and sustainability. Clinically, MIC may efficiently inform care and improve outcomes through effective use of data (5, 6). Organizationally, a tightly curated and payer-aligned measure set can reduce burden from competing clinical, quality, accountability, and fiscal reporting practices (1, 2). Aligned and synthesizable data sets can illustrate the impact of behavioral health services nationwide, which can help attract investment in behavioral health care (1, 2).
Our two-tier approach to prioritizing MIC measures serves as a template for immediate actions (tier 1) and future innovations (tier 2). Tier 1 is feasible and meaningful because it makes use of measures that many behavioral health organizations already use, directs quality measurement bodies to modify specifications in order to lower clinician and system burden, and provides a concise set of measures that the field can include when exploring sustainability strategies such as value-based payment. Our approach to tier 2, in which we propose concepts and candidate measures instead of advocating for specific widely used scales, reflects the state of the field, and shows the need for significant field testing before these new or updated measures are endorsed by national organizations that direct how care is measured and reported.

Acknowledgments

The authors acknowledge Senior Project Manager Tiffany Francis and other NCMW collaborators, including members of the expert panel. The authors also acknowledge session participants of the NatCon23 meeting in Los Angeles on May 3, 2023, and of the Substance Abuse and Mental Health Services Administration lunch-and-learn on May 30, 2023, who provided input on the project.

Supplementary Material

File (appi.ps.20240082.ds001.pdf)

References

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Alter CL, Mathias A, Zahniser J, et al: Measurement-Based Care in the Treatment of Mental Health and Substance Use Disorders. Dallas, Meadows Mental Health Policy Institute, 2021. https://mmhpi.org/wp-content/uploads/2021/03/MBC_Report_Final.pdf
2.
Ridout KK, Vanderlip ER, Ridout SJ, et al: Measurement-based care implementation challenges and opportunities in real-world practice. Psychiatr Ann 2023; 53:405–409
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American Diabetes Association: 6. Glycemic targets: standards of medical care in diabetes—2020. Diabetes Care 2020; 43:S66–S76
4.
Quality Measures for Behavioral Health Clinics: Technical Specifications and Resource Manual. Rockville, MD, Substance Abuse and Mental Health Services Administration, 2024. https://www.samhsa.gov/sites/default/files/ccbhc-quality-measures-technical-specifications-manual.pdf
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Fortney JC, Unützer J, Wrenn G, et al: A tipping point for measurement-based care. Psychiatr Serv 2017; 68:179–188
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Lambert MJ, Whipple JL, Kleinstäuber M, et al: Collecting and delivering progress feedback: a meta-analysis of routine outcome monitoring. Psychotherapy 2018; 55:520–537
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Tartakovsky M: Feedback-Informed Treatment: Empowering Clients to Use Their Voices. Fort Mill, SC, PsychCentral, 2016. https://psychcentral.com/lib/feedback-informed-treatment-empowering-clients-to-use-their-voices#1. Accessed Aug 2, 2024
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Wrenn G, Fortney J: A Core Set of Outcome Measures for Behavioral Health Across Service Settings. Washington, DC, Kennedy Forum, 2015. https://pjk-wp-uploads.s3.amazonaws.com/www.thekennedyforum.org/uploads/2017/06/MBC_supplement.pdf
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Shahid R, Shoker M, Chu LM, et al: Impact of low health literacy on patients’ health outcomes: a multicenter cohort study. BMC Health Serv Res 2022; 22:1148
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Chung H, Scharf D, Parks J, et al: Advancing Measurement-Informed Care in Community Behavioral Health. Washington, DC, National Council for Mental Wellbeing, 2024. https://www.thenationalcouncil.org/wp-content/uploads/2024/02/24.02.15_MDI-Measurement-Informed-Care-Report.pdf
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Brown J, Hudson Scholle S, Croake S, et al: Development and Testing of Behavioral Health Quality Measures for Health Plans: Final Report. Washington, DC, US Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, 2018. https://aspe.hhs.gov/reports/development-testing-behavioral-health-quality-measures-health-plans-final-report-0. Accessed Aug 2, 2024
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Measures in Mental and Behavioral Health Registry. Washington, DC, APA Services Inc, 2018. https://www.apaservices.org/practice/reimbursement/health-registry/measures. Accessed Aug 2, 2024
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Follow-Up Care for Adult Medicaid Beneficiaries Who Are Newly Prescribed an Antipsychotic Medication Measure (NQF 3313). Baltimore, Centers for Medicare and Medicaid Services, 2021. https://www.medicaid.gov/state-resource-center/innovation-accelerator-program/iap-downloads/functional-areas/techspecsmanual-nqf-3313.pdf?t=1685575925
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Core Set of Health Home Quality Measures for 1945 Medicaid Health Home Programs (1945 Health Home Core Set), 2013–2024. Baltimore, Centers for Medicare and Medicaid Services, 2023. https://www.medicaid.gov/sites/default/files/2023-03/2023-health-home-core-set-history-table.pdf
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DuBard A, Israel J, Mostashari F, et al: Less Is More: Quality Measurement in Primary Care. Washington, DC, Health Affairs, 2023. https://www.healthaffairs.org/do/10.1377/forefront.20230614.546595/full. Accessed Aug 2, 2024

Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services
Psychiatric Services
PubMed: 39188149

History

Received: 16 February 2024
Revision received: 3 June 2024
Revision received: 8 July 2024
Accepted: 16 July 2024
Published online: 27 August 2024

Keywords

  1. Measurement informed care (MIC)
  2. Measurement based care (MBC)
  3. Community behavioral health
  4. Outcome and clinical measurement
  5. Community mental health services

Authors

Details

Deborah Scharf, Ph.D. [email protected]
National Council for Mental Wellbeing (NCMW), Washington, D.C. (all authors); Department of Psychology, Lakehead University, Thunder Bay, Ontario (Scharf); Department of Psychiatry, Albert Einstein College of Medicine, New York City (Chung); Missouri Institute of Mental Health, University of Missouri, St. Louis (Parks).
Henry Chung, M.D.
National Council for Mental Wellbeing (NCMW), Washington, D.C. (all authors); Department of Psychology, Lakehead University, Thunder Bay, Ontario (Scharf); Department of Psychiatry, Albert Einstein College of Medicine, New York City (Chung); Missouri Institute of Mental Health, University of Missouri, St. Louis (Parks).
Joseph Parks, M.D.
National Council for Mental Wellbeing (NCMW), Washington, D.C. (all authors); Department of Psychology, Lakehead University, Thunder Bay, Ontario (Scharf); Department of Psychiatry, Albert Einstein College of Medicine, New York City (Chung); Missouri Institute of Mental Health, University of Missouri, St. Louis (Parks).

Notes

Send correspondence to Dr. Scharf ([email protected]).

Competing Interests

Dr. Scharf reports receiving consulting fees from NCMW. Dr. Chung reports being a consultant to Valera Health, McKinsey and Company, and NCMW. Dr. Parks reports being a consultant to Boehringer Ingelheim.

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