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To improve quality, keep your eyes on the road
  1. Marc Philip T Pimentel1,2,
  2. John Matthew Austin3,4,
  3. Allen Kachalia4,5
  1. 1 Department of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
  2. 2 Department of Quality and Safety, Brigham and Women’s Hospital, Boston, Massachusetts, USA
  3. 3 Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
  4. 4 Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
  5. 5 Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
  1. Correspondence to Dr Marc Philip T Pimentel, Anesthesiology, Brigham and Women's Hospital, Boston, MA 02115, USA; mppimentel{at}bwh.harvard.edu

https://doi.org/10.1136/bmjqs-2020-011102

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    In healthcare quality improvement, we are trained to believe that, “every system is perfectly designed to get the results it gets”.1 By focusing relentlessly on getting the process right, we will know we can arrive at better outcomes.2 Over the past decade, however, publicly reported metrics for hospitals have moved away from process metrics, further emphasising outcome metrics. The Centers for Medicare and Medicaid Services (CMS) has major pay-for-performance programmes for hospitals aimed squarely at improving outcomes, such as hospital-acquired infections and 30-day readmission rates. US News and World Report’s and Leapfrog’s hospital rankings heavily weight outcomes, such as 30-day mortality rates and postoperative complications. In this viewpoint, we propose that although process measures have had limitations that led to the shift towards outcome measures, new developments in electronic health records, data collection, and quality measurement have the potential to overcome these limitations and vastly improve the utility of process measures.

    The rationale for shifting towards outcome measures is more than reasonable, as process measures have had their challenges. If performance on a process measure improves (eg, increased haemoglobin A1c testing for diabetes management) but is not accompanied by sufficient resulting improvements in outcomes (eg, haemoglobin A1c results meeting desired levels), it may not make sense to continue optimising performance on that process measure.3 4

    Also, seeking improvement in process measures, if not carefully constructed, may not always lead to meaningful changes in the clinical process. One notable example is smoking cessation counselling at discharge. A hospital could meet the smoking cessation counselling measure by simply adding to every discharge summary an instruction that says, “If you smoke, we advise you to stop”. As a result of the lack of meaningful change in clinical practice, that tobacco cessation measure was subsequently dropped. A more stringent measure was …

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    Footnotes

    • Twitter @MarcPimentelMD

    • Contributors All three authors were involved with the following contributions: substantial contributions to the conception or design of the work; drafting the work or revising it critically for important intellectual content; final approval of the version published; agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. We would like to thank Chris Holzmueller for help with an early draft of this manuscript.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement There are no data in this work.