Skip to main content
Effective Health Care Program
Home » Products » Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression » Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression

Outcome Measure Harmonization and Data Infrastructure for Patient-Centered Outcomes Research in Depression

Research Report Draft

Open for comment through Apr 29, 2021

This draft report is available in electronic format only (Draft Report, [PDF, 1.8 MB]). For additional assistance, please contact us.



Patient registries provide valuable information to describe the course of a disease, understand treatment patterns and outcomes, examine the effectiveness, safety, and value of products and interventions, and measure and improve quality of care. A patient registry is defined as "an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure and that serves one or more pre-determined scientific, clinical, or policy purposes."1

Patient registries fulfill different purposes for a wide range of stakeholders, as documented in the publication, Registries for Evaluating Patient Outcomes: A User's Guide.1 For clinicians, registries that collect data on disease course and outcomes in large patient populations can provide information on current treatment practices and outcomes to inform decision-making. Clinicians may participate in registries to engage in research, complete maintenance of certification requirements, and/or collect and report quality measures, such as those required under the Merit-based Incentive Payment System (MIPS). Recently, many efforts in the United States have focused on the potential role of registries as the foundation of research data infrastructure and learning health systems. Registries can be a central component of these systems by providing data and tools to support population health management, clinical decision-making, quality improvement, research, and collection of patient-reported outcomes (PROs). Many professional associations have developed registries to support the needs of their clinicians. For example, the PRIME Registry2 and PsychPRO3 are designed to help clinicians meet quality reporting requirements under MIPS and track and manage patient outcomes through progress reports and clinical decision support tools. In some cases, registries such as these have provided data for research purposes as well.

While many registries serve multiple purposes, some are designed specifically for clinical research and safety surveillance. Drug and device manufacturers use registries to inform the development of new products by gathering information on treatment patterns and patient populations. For marketed products, registries can provide real-world evidence (RWE) of product performance to support reimbursement decisions and help manufacturers meet post-marketing commitments. The passage of the 21st Century Cures Act4 in 2016 generated new interest in registries as a source of real-world data and RWE to inform regulatory decision-making. The U.S. Food and Drug Administration (FDA) identified registries as a source of real-world data in its framework for RWE; some registries have already been used as a source of real-world data to support regulatory decision-making. The FDA also uses data from registries under the National Evaluation System for Health Technology (NEST) project.5 While typically not registry sponsors, public and private payers use registry data to track how devices, procedures, or pharmaceutical products are used in practice and to monitor effectiveness in different populations; of note, the Centers for Medicare and Medicaid Services (CMS) uses registry data for decisions under the Coverage with Evidence Development program.6

Other sponsors and users of registry data include patient advocacy groups, academic researchers, and public health professionals. Patient advocacy groups may sponsor or participate in registry development to increase understanding of the natural history of a disease and to support efforts to develop new treatments; this is particularly common for rare diseases. Academic researchers use registries for a wide range of purposes, such as tracking long-term patient outcomes, examining the effectiveness or comparative effectiveness of procedures or therapies, investigating genetic or environmental factors related to specific diseases, or examining the role of new technologies. For public health professionals, registries provide an important tool for monitoring prevalence and incidence of diseases and tracking the impact of public health interventions.

Given their myriad purposes, it is unsurprising that a large number of registries exist—over 7,300 according to Together, registries represent an enormous investment in research infrastructure and a tremendous data resource that could be used to address new research questions in a timely and efficient manner. Registries also occupy a unique role in the health data landscape, in that they capture data across all components of a learning health system. Registries provide a bridge connecting research and clinical practice, and they can offer tools to support clinical decision-making at the individual patient level and data to support population health management and quality improvement initiatives. Yet, the value of registries as a foundation for research data infrastructure and learning health systems is currently limited by the variation in the data collected in different registries, even within the same clinical areas. This variation makes it more challenging to reuse registry data for other purposes, and at the same time increases the burden of data collection at the clinician and registry level.

The development and implementation of core sets of standardized outcome measures in patient registries and clinical care would address these challenges and enable registries to realize their potential as the foundation for learning health systems and research data infrastructure. For example, use of standardized outcome measures in registries would create opportunities to compare, link, and aggregate registry data to address new research questions, while use of standardized outcome measures in clinical practice would create opportunities to compare outcomes across care settings and better compare the outcomes achieved in real-world settings with those reported in research studies. To realize this vision, the Agency for Healthcare Research and Quality (AHRQ) has supported the creation of the Outcome Measures Framework (OMF), a conceptual model for classifying outcomes that are relevant to patients and clinicians across most conditions,7 and the use of the OMF to develop standardized outcome measures in five clinical areas.8-13

The purpose of this project was to assess the feasibility and value of implementing standardized outcome measures in multiple care settings, using the harmonized depression outcome measures as a test case.11 Major depressive disorder (MDD) is a common mental disorder that affects an estimated 16.2 million adults and 3.1 million adolescents in the United States.14 Characterized by changes in mood, cognitive function, and/or physical function that persist for two or more weeks, MDD can reduce quality of life substantially, impair function at home, work, school, and in social settings, and result in increased mortality.15 Research on depression diagnosis, treatments, and outcomes is complicated by heterogeneity in care settings and treatment approaches. Clinicians use different instruments, such as the Patient Health Questionnaire-9 (PHQ-9)16 and the Hamilton Depression Rating Scale (HAM-D),17 to assess symptom severity and different definitions and different timeframes to measure concepts such as remission, response to treatment, and recurrence.

The harmonized depression outcome measures developed under the prior project (Appendix A) provide a core set of harmonized definitions intended for use in routine clinical care across care settings and to support patient-centered outcomes research.


  1. Gliklich RE, Leavy MB, Dreyer NA (sr eds). Registries for Evaluating Patient Outcomes: A User’s Guide. 4th ed. (Prepared by L&M Policy Research, LLC, under Contract No. 290-2014-00004-C with partners OM1 and IQVIA) AHRQ Publication No. 19(20)-EHC020. Rockville, MD: Agency for Healthcare Research and Quality; September 2020. DOI: 10.23970/AHRQEPCREGISTRIES4.
  2. PRIME Registry. American Board of Family Medicine. Accessed March 15, 2021.
  3. PsychPRO. American Psychiatric Association. Accessed March 15, 2021.
  4. 21st Century Cures Act, Public Law 114-255, 114th Cong., 2d sess. December 13, 2016. Accessed March 15, 2021.
  5. U.S. Food and Drug Administration. National Evaluation System for Health Technology (NEST). Accessed March 15, 2021.
  6. Centers for Medicare & Medicaid Services. Guidance for the Public, Industry, and CMS Staff. Coverage with Evidence Development. November 20, 2014. Accessed March 15, 2021.
  7. Gliklich RE, Leavy MB, Karl J, et al. A framework for creating standardized outcome measures for patient registries. Journal of comparative effectiveness research. 2014;3(5):473-80.
  8. Leavy MB, Schur C, Kassamali FQ, Johnson ME, Sabharwal R, Wallace P, Gliklich RE. Development of Harmonized Outcome Measures for Use in Patient Registries and Clinical Practice: Methods and Lessons Learned. Final Report. (Prepared by L&M Policy Research, LLC under Contract No. 290-2014-00004-C) AHRQ Publication No. 19-EHC008-EF. Rockville, MD: Agency for Healthcare Research and Quality; February 2019. DOI: 10.23970/AHRQEPCLIBRARYFINALREPORT.
  9. Calkins H, Gliklich RE, Leavy MB, et al. Harmonized outcome measures for use in atrial fibrillation patient registries and clinical practice: Endorsed by the Heart Rhythm Society Board of Trustees. Heart Rhythm. 2019;16(1):e3-e16.
  10. Gliklich RE, Castro M, Leavy MB, et al. Harmonized outcome measures for use in asthma patient registries and clinical practice. J Allergy Clin Immunol. 2019;144(3):671-81.e1.
  11. Gliklich RE, Leavy MB, Cosgrove L, et al. Harmonized Outcome Measures for Use in Depression Patient Registries and Clinical Practice. Ann Intern Med. 2020;172(12):803-9.
  12. Harbaugh RE, Devin C, Leavy MB, et al. Harmonized Outcome Measures for Use in Degenerative Lumbar Spondylolisthesis Patient Registries and Clinical Practice. J Neurosurg Spine. Forthcoming 2021.
  13. Edelman MJ, Raymond DP, Owen DH, et al. Harmonized Outcome Measures for Use in Non-Small Cell Lung Cancer Patient Registries and Clinical Practice. J Natl Compr Canc Netw. Forthcoming 2021.
  14. Brody DJ, Pratt LA, Hughes J. Prevalence of depression among adults aged 20 and over: United States, 2013–2016. NCHS Data Brief, no 303. Hyattsville, MD: National Center for Health Statistics. 2018.
  15. Machado MO, Veronese N, Sanches M, et al. The association of depression and all-cause and cause-specific mortality: an umbrella review of systematic reviews and meta-analyses. BMC Med. 2018;16(1):112.
  16. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606-13.
  17. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56-62.