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Quality Measures in Heart Failure: the Past, the Present, and the Future

  • Carisi A. PolanczykEmail author
  • Karen B. Ruschel
  • Fabio Morato Castilho
  • Antonio L. Ribeiro
Implementation (L Rhode, Section Editor)
  • 57 Downloads
Part of the following topical collections:
  1. Topical Collection on Implementation

Abstract

Purpose of Review

This paper reviews performance measure in health, their importance, and methodologic issues, focusing on metrics for health failure patients. Quality measures are instruments to assess structural aspects or processes of care aiming to guarantee that optimal patient outcomes are achieved. As heart failure is a chronic condition in which established therapies reduce mortality and hospital admissions, there are quite a lot of initiatives that aim to monitor for quality of care and to coordinate the disease management.

Recent Findings

Several performance measures were validated for these patients, from process of care (left ventricular function assessment and use of ACEi/ARBs and beta-blockers) to health outcomes (hospital mortality and readmissions). In the early years, studies demonstrated a relationship between quality measurements and health outcomes. Nonetheless, more recent ones based on large databases of patients’ medical records have shown that traditional indicators explain only a small fraction of health and patient reported- and perceived outcomes. Public reporting of quality measures and payment conditioned to the quality of care provided were not able to show benefit in terms of hard outcomes. Data science and big data methods are promising in providing actionable knowledge for quality improvement, with real-time data that could support decision-making.

Summary

Heart failure is a chronic condition that has proven to be useful for measuring medical and healthcare quality. Evidence-based indicators have already reached high rates of adherence and are currently poorly correlated with outcomes. Using real-life data and based on the patient’s perspective can be useful tools to improve these indicators.

Keywords

Quality of care Health indicators Heart failure Outcome Readmission Big data 

Notes

Compliance With Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Centers for Medicare & Medicaid Services (CMS). [Accessed March 27, 2014] Medicare Health Support. 2012. https://www.cms.gov/Medicare/Medicare-General-Information/CCIP/.
  2. 2.
    Krumholz HM, Lin Z, Keenan PS, Chen J, Ross JS, Drye EE, et al. Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia. JAMA. 2013;309:587–93.CrossRefGoogle Scholar
  3. 3.
    Feltner C, Jones CD, Cene CW, et al. Transitional care interventions to prevent readmissions for persons with heart failure: a systematic review and meta-analysis. Ann Intern Med. 2014;160(11):774–84.CrossRefGoogle Scholar
  4. 4.
    Spatz ES, Lipska KJ, Dai Y, Bao H, Lin Z, Parzynski CS, et al. Risk-standardized acute admission rates among patients with diabetes and heart failure as a measure of quality of accountable care organizations: rationale, methods, and early results. Med Care. 2016;54(5):528–37.CrossRefGoogle Scholar
  5. 5.
    Smith PC, Mossialos E, Papanicolas I. Performance measurement for health system improvement: experiences, challenges and prospects. World Health Organization 2008 and World Health Organization, on behalf of the European Observatory on Health Systems and Policies. 2008. 18p.Google Scholar
  6. 6.
    • López-Sendón J, González-Juanate JR, Pinto F, et al. Quality markers in cardiology. Main markers to measure quality of results (outcomes) and quality measures related to better results in clinical practice (performance metrics). A SEC/SECTCV Consensus Position Paper. Rev Esp Cardiol. 2015;68(11):976–995.e10 This position paper provides an overview of quality indicators in cardiology for institutions in Spain. CrossRefGoogle Scholar
  7. 7.
    Goldfarb M, Bibas L, Newby LK, Henry TD, Katz J, van Diepen S, et al. Systematic review and directors survey of quality indicators for the cardiovascular intensive care unit. Int J Cardiol. 2018;260:219–25.CrossRefGoogle Scholar
  8. 8.
    Bonow RO, Ganiats TG, Beam CT, Blake K, Casey de Jr, Goodlin SJ, et al. ACCF/AHA/AMA-PCPI 2011 performance measures for adults with heart failure: a report of the American College of Cardiology Foundation/American Heart Association task force on performance measures and the American Medical Association–physician consortium for performance improvement. Circulation. 2012;125:2382–401.CrossRefGoogle Scholar
  9. 9.
    Fonarow GC, Abraham WT, Albert NM, Stough WG, Gheorghiade M, Greenberg BH, et al. Association between performance measures and clinical outcomes for patients hospitalized with heart failure. JAMA. 2007;297(1):61–70.CrossRefGoogle Scholar
  10. 10.
    Hernandez AF, Hammill BG, Peterson ED, Yancy CW, Schulman KA, Curtis LH, et al. Relationships between emerging measures of heart failure processes of care and clinical outcomes. Am Heart J. 2010;159(3):406–13.CrossRefGoogle Scholar
  11. 11.
    Chen LM, Staiger DO, Birkmeyer JD, Ryan AM, Zhang W, Dimick JB. Composite quality measures for common inpatient medical conditions. Med Care. 2013;51(9):832–7.CrossRefGoogle Scholar
  12. 12.
    Dy SM, Chan KS, Chang H-Y, Zhang A, Zhu J, Mylod D. Patient perspectives of care and process and outcome quality measures for heart failure admissions in US hospitals: how are they related in the era of public reporting? Int J Qual Health Care. 2016;28(4):522–8.CrossRefGoogle Scholar
  13. 13.
    Gheorghiade M, Vaduganathan M, Fonarow GC, Bonow RO. Rehospitalization for heart failure: problems and perspectives. J Am Coll Cardiol. 2013;61(4):391–403.CrossRefGoogle Scholar
  14. 14.
    • Fischer C, Steyerberg FW, Fonarow GC, et al. A systematic review and meta-analysis on the association between quality of hospital care and readmission rates in patients with heart failure. Am Heart J. 2015;170:1005–17 A comprehensive systematic review on the association between quality of hospital care and readmission rates in patients with heart failure.CrossRefGoogle Scholar
  15. 15.
    Moertl D, Altenberger J, Bauer N, Berent R, Berger R, Boehmer A, et al. Disease management programs in chronic heart failure: position statement of the heart failure working group and the Working Group of the Cardiological Assistance and Care Personnel of the Austrian Society of Cardiology. Wien Klin Wochenschr. 2017;129(23–24):869–78.CrossRefGoogle Scholar
  16. 16.
    Fonarow GC, Peterson ED. Heart failure performance measures and outcomes. Real or Illusory gains. JAMA. 2009;302:792–4.CrossRefGoogle Scholar
  17. 17.
    Glance LG, Li Y, Dick AW. Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone. BMC Health Serv Res. 2017;17:327–36.CrossRefGoogle Scholar
  18. 18.
    Gupta A, Fonarow GC. The Hospital Readmissions Reduction Program-learning from failure of a healthcare policy. Eur J Heart Fail. 2018;20(8):1169–74.CrossRefGoogle Scholar
  19. 19.
    Gupta A, Allen LA, Bhatt DL, Cox M, DeVore AD, Heidenreich PA, et al. Association of the hospital readmissions reduction program implementation with readmission and mortality outcomes in heart failure. JAMA Cardiol. 2018;3(1):44–53.CrossRefGoogle Scholar
  20. 20.
    Garin O, Ferrer M, Pont A, Rué M, Kotzeva A, Wiklund I, et al. Disease-specific health-related quality of life questionnaires for heart failure: a systematic review with meta-analyses. Qual Life Res. 2009;18:71–85.CrossRefGoogle Scholar
  21. 21.
    International Consortium for Health Outcomes Measurement. http://www.ichom.org/medical-conditions/heart-failure/. Accessed in 24 Sept 2018.
  22. 22.
    Doan S, Bastarache L, Klimkowski S, Denny JC, Xu H. Integrating existing natural language processing tools for medication extraction from discharge summaries. J Am Med Inform Assoc. 2010;17(5):528–31.CrossRefGoogle Scholar
  23. 23.
    •• Meystre SM, Kim Y, Gobbel GT, et al. Congestive heart failure information extraction framework for automated treatment performance measures assessment. J Am Med Inform Assoc. 2017;24(e1):e40–e6 A study describing automated extraction of healthcare indicators from medical record, a transition to use of bigdata in practice. PubMedGoogle Scholar
  24. 24.
    Tu JV, Chu A, Donovan LR, Ko DT, Booth GL, Tu K, et al. The Cardiovascular Health in Ambulatory Care Research Team (CANHEART): using big data to measure and improve cardiovascular health and healthcare services. Circ Cardiovasc Qual Outcomes. 2015;8(2):204–12.CrossRefGoogle Scholar
  25. 25.
    Garvin JH, Kim Y, Gobbel GT, Matheny ME, Redd A, Bray BE, et al. Automating quality measures for heart failure using natural language processing: a descriptive study in the Department of Veterans Affairs. JMIR Med Inform. 2018;6(1):e5.CrossRefGoogle Scholar
  26. 26.
    Golas SB, Shibahara T, Agboola S, Otaki H, Sato J, Nakae T, et al. A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data. BMC Med Inform Decis Mak. 2018;18(1):44.CrossRefGoogle Scholar
  27. 27.
    Fung CH, Lim YW, Mattke S, Damberg C, Shekelle PG. Systematic review: the evidence that publishing patient care performance data improves quality of care. Ann Intern Med. 2008;148(2):111–23.CrossRefGoogle Scholar
  28. 28.
    Ryan AM, Nallamothu BK, Dimick JB. Medicare’s public reporting initiative on hospital quality had modest or no impact on mortality from three key conditions. Health Aff (Millwood). 2012;31(3):585–92.CrossRefGoogle Scholar
  29. 29.
    Ryan AM, Krinsky S, Maurer KA, Dimick JB. Changes in hospital quality associated with hospital value-based purchasing. N Engl J Med. 2017;376(24):2358–66.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Carisi A. Polanczyk
    • 1
    • 2
    • 3
    Email author
  • Karen B. Ruschel
    • 1
    • 2
  • Fabio Morato Castilho
    • 1
    • 4
  • Antonio L. Ribeiro
    • 1
    • 4
  1. 1.National Institute of Science and Technology for Health Technology Assessment (IATS), CNPqPorto AlegreBrazil
  2. 2.Graduate Program in Cardiology and Cardiovascular SciencesUniversidade Federal do Rio Grande do SulPorto AlegreBrazil
  3. 3.Cardiology CenterHospital Moinhos de VentoPorto AlegreBrazil
  4. 4.Hospital das Clínicas and School of MedicineUniversidade Federal Minas GeraisBelo HorizonteBrazil

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