Purpose, Subject, and Consumer; Comment on “Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study”

Document Type : Commentary


1 VA HSR&D Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA

2 Department of Medicine, Health Services Research Section, Baylor College of Medicine, Houston, TX, USA

3 Epidemiology and Health Outcomes Research Unit, Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine and Lucile Packard Children’s Hospital, Palo Alto, CA, USA

4 California Perinatal Quality Care Collaborative, Palo Alto, CA, USA


Zegers and colleagues’ study codifies the perceived burden of quality monitoring and improvement stemming from the work by clinicians of registering (documenting) quality information in the medical record. We agree with Zegers and colleagues’ recommendation that a smaller, more effective and curated set of measures is needed to reduce burden, confusion, and expense. We further note that focusing on validity of clinical evidence behind individual measures is critical, but insufficient. We therefore extend Zegers and colleagues’ work through a pragmatic, tripartite heuristic. To assess the value of and curate a targeted set of performance measures, we propose concentrating on the relationships among three factors: (1) The purpose of the performance measure, (2) the subject being evaluated, and (3) the consumer using information for decision-making. Our proposed tripartite framework lays the groundwork for executing the evidence-based recommendations proposed by Zegers et al, and provides a path forward for more effective healthcare performance-measurement systems.


  • epublished Author Accepted Version: January 30, 2022
  • epublished Final Version: February 9, 2022
  1. Agency for Healthcare Research and Quality. National Quality Measures Clearinghouse. 5/17/2010. Available from: http://www.qualitymeasures.ahrq.gov.
  2. Zegers M, Veenstra GL, Gerritsen G, Verhage R, van der Hoeven HJG, Welker GA. Perceived burden due to registrations for quality monitoring and improvement in hospitals: a mixed methods study. Int J Health Policy Manag. 2022;11(2):183-196. doi:34172/ijhpm.2020.96
  3. Blumenthal D, McGinnis JM. Measuring vital signs: an IOM report on core metrics for health and health care progress. JAMA. 2015;313(19):1901-1902. doi:1001/jama.2015.4862
  4. Casalino LP, Gans D, Weber R, et al. US physician practices spend more than $15.4 billion annually to report quality measures. Health Aff (Millwood). 2016;35(3):401-406. doi:1377/hlthaff.2015.1258
  5. Rogut L, Kothari P, Audet AM. Empowering New Yorkers with Quality Measures That Matter to Them. Quality Institute, United Hospital Fund; 2017.
  6. Schuster MA, Onorato SE, Meltzer DO. Measuring the cost of quality measurement: a missing link in quality strategy. JAMA. 2017;318(13):1219-1220. doi:1001/jama.2017.11525
  7. Evans SM, Lowinger JS, Sprivulis PC, Copnell B, Cameron PA. Prioritizing quality indicator development across the healthcare system: identifying what to measure. Intern Med J. 2009;39(10):648-654. doi:1111/j.1445-5994.2008.01733.x
  8. Stelfox HT, Straus SE. Measuring quality of care: considering measurement frameworks and needs assessment to guide quality indicator development. J Clin Epidemiol. 2013;66(12):1320-1327. doi:1016/j.jclinepi.2013.05.018
  9. Stelfox HT, Straus SE. Measuring quality of care: considering conceptual approaches to quality indicator development and evaluation. J Clin Epidemiol. 2013;66(12):1328-1337. doi:1016/j.jclinepi.2013.05.017
  10. Chassin MR, Loeb JM, Schmaltz SP, Wachter RM. Accountability measures--using measurement to promote quality improvement. N Engl J Med. 2010;363(7):683-688. doi:1056/NEJMsb1002320
  11. Nothacker M, Stokes T, Shaw B, et al. Reporting standards for guideline-based performance measures. Implement Sci. 2016;11:6. doi:1186/s13012-015-0369-z
  12. National Quality Forum (NQF). Maximizing the Value of Measurement: MAP 2017 Guidance 2017. NQF; 2017.
  13. Prentice JC, Frakt AB, Pizer SD. Metrics that matter. J Gen Intern Med. 2016;31 Suppl 1:70-73. doi:1007/s11606-015-3559-0
  14. ABIM Foundation. Choosing Wisely. 2022. Available from: choosingwisely.org.
  15. Meltzer DO, Chung JW. The population value of quality indicator reporting: a framework for prioritizing health care performance measures. Health Aff (Millwood). 2014;33(1):132-139. doi:1377/hlthaff.2011.1283
  16. Pronovost PJ. High-performing health care delivery systems: high performance toward what purpose? Jt Comm J Qual Patient Saf. 2017;43(9):448-449. doi:1016/j.jcjq.2017.06.001
  17. Kane JS. Performance distribution assessment. In: Berk RA, ed. Performance Assessment: Methods and Applications. Baltimore: Johns Hopkins University Press; 1986. p. 237-73.
  18. Committee on Quality of Health Care in America. Performance Measurement: Accelerating Improvement. Washington, DC: National Academies Press; 2006.
  19. Prichard RD, Weaver SJ, Ashwood EL. Evidence-Based Productivity Improvement: A Practical Guide to the Productivity Measurement and Enhancement System. New York: Routledge Academic; 2011.
  20. Aguinis H. An expanded view of performance management. In: Smither JW, London M eds. Performance Management: Putting Research into Action. The professional practice series. San Francisco, CA: Jossey-Bass; 2009. p. 1-43.
  21. Hysong SJ, Francis J, Petersen LA. Motivating and engaging frontline providers in measuring and improving team clinical performance. BMJ Qual Saf. 2019;28(5):405-411. doi:1136/bmjqs-2018-008856
  22. Hysong SJ, Amspoker AB, Hughes AM, et al. Improving team coordination in primary-care settings via multifaceted team-based feedback: a non-randomised controlled trial study. BJGP Open. 2021;5(2). doi:3399/bjgpo.2020.0185
Volume 11, Issue 4
April 2022
Pages 539-543
  • Receive Date: 16 June 2021
  • Revise Date: 27 January 2022
  • Accept Date: 29 January 2022
  • First Publish Date: 30 January 2022