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\begin{document}

\title{The future of deprescribing research: seizing opportunities and learning
from the past}



\author[1]{Michael Steinman}%
\affil[1]{University of California San Francisco}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\textbf{The future of deprescribing research: seizing opportunities and
learning from the past}

Michael A. Steinman, MD

University of California, San Francisco and the San Francisco VA Medical
Center

Word count: 1549

References: 10

Funding: This work was supported by the National Institute on Aging
(grants R24AG064025 and K24AG049057)

Disclosures: Dr. Steinman receives royalties from UpToDate and honoraria
from the American Geriatrics Society. This manuscript is based on a
lecture given at the First International Conference on Deprescribing
(ICOD), Kolding, Denmark, September 2022.

\emph{Corresponding author:}

Michael Steinman, MD

4150 Clement St Box 181G

San Francisco CA 94121 mike.steinman@ucsf.edu

Fax 415.750.6641

Tel 415.221.4810 x23677

There is much to celebrate about deprescribing research. The past decade
has seen an explosion of interest in the topic.\textsuperscript{1}Recent
scholarship has revealed key barriers and facilitators to deprescribing,
elucidated effective communication strategies, and developed new
measures. Moreover, it has demonstrated the potential for deprescribing
to improve outcomes, with meta-analyses finding that intensive
deprescribing interventions may reduce mortality and falls in nursing
homes by approximately 25\%, and that comprehensive medical review may
yield similar reductions in mortality among older adults in ambulatory
settings.\textsuperscript{2,3}

Yet, challenges abound. Many interventions which seemed promising have
had disappointing results, and we have gained appreciation of how
difficult deprescribing can be. In clinical practice, many people are
reluctant to stop medications they were previously told they needed, and
clinicians often lack incentive, willingness, or adequate time to make
proactive efforts to deprescribe. Even when successful, real-world
translation of interventions remains limited, and the push for
aggressive medication therapy remains deeply embedded in health systems.
Reducing medication count, a common outcome of studies, is not
necessarily a win for patients if the discontinued medications were not
bothersome or costly to them or their caregivers.

Deprescribing research is thus at a crossroads. While we celebrate
initial successes, the easiest work is behind us. As we look ahead, I
offer 6 recommendations for how the field can continue to grow,
developed from my own reflections, conversations with leaders in the
field, and past literature\textsuperscript{4} and initially presented as
a talk at the first International Conference on Deprescribing in
September 2022.

\textbf{Recommendation \#1: Keep doing the ``basic science'' of
deprescribing and use it to inform interventions}

Like most scientific endeavors, deprescribing has a translational
pathway, beginning with understanding fundamental questions and using
the answers to these questions to inform intervention development,
testing, and dissemination. Examples of foundational questions include
what are the medication problems that merit attention, who has these
problems, what stimulates and motivates patients and clinicians to
deprescribe in different clinical settings, and what are the right
outcomes to measure.

Unfortunately, we have often skipped to designing and testing
interventions without fully understanding these upstream questions,
resulting in less effective interventions and evaluating the wrong
outcomes when we study them. Some aspects of the ``basic science'' of
deprescribing, for example evaluating barriers and facilitators, have
been extensively studied. Yet, we have much to learn about many other
foundational questions and how to incorporate these learnings into
interventions.

\textbf{Recommendation \#2: Lean into behavior change -- or bypass it}

In many cases, deprescribing is a type of behavior change more akin to
promoting smoking cessation than ordering an X-ray or new medication. It
requires engaging with patients to stop a medication to which they may
have become psychologically or physically attached and enacting that
behavior. It also requires convincing overworked and time-pressed
clinicians to engage in conversations that may be difficult and
time-consuming and to incorporate these actions into their daily
clinical practice.

Thus, it is important for interventions to lean into the science and
practice of behavior change. A superb example of this is the brochures
developed for and tested in the EMPOWER and D-PRESCRIBE trials, which
thoughtfully incorporate principles of health psychology and behavior
change.\textsuperscript{5} Yet, relatively few interventions have
followed this lead to incorporate key behavior change
elements.\textsuperscript{6}

In a notable exception, under the right conditions health system
mandates can offer the opportunity to bypass behavior change. This can
arise when systems-level changes reduce or obviate the need for action
by patients or clinicians. An example of this is policy changes during
early phases of the COVID pandemic which temporarily discontinued
non-essential medications in nursing home
residents.\textsuperscript{7}Ethical and legal considerations limit such
top-down directives, but in selected circumstances they offer novel
opportunities for scholarship and improvement.

\textbf{Recommendation \#3: Be strategic about outcomes}

Investigators conducting deprescribing trials often wish to determine
the effect of their interventions on ``big-ticket'' outcomes such as
mortality, hospitalization, and quality of life. We can do ourselves a
disservice by reaching for these endpoints, as we will often fall short.
Given how many factors outside of medication use impact these outcomes,
deprescribing interventions may need to have unrealistically potent
effects to detect a difference given the limited sample sizes we
typically employ. Consider cardiology trials, which often enroll tens of
thousands of patients over multiple years to try and achieve such
outcomes. And, contrast this with drugs like ezetimibe, which was
approved by the US Food and Drug Administration on the basis of
beneficial effects on lipid levels without any data on cardiovascular
morbidity or mortality.\textsuperscript{8} If this is the evidence
required to generate widespread use of a drug with well over \$1 billion
in sales, we may be setting too ambitious a standard for ourselves to
attain.

An interesting contrast is set by the OPTIMIZE trial, which used a
non-inferiority design and was published in \emph{JAMA} with substantial
attention. This study showed that older adults with well-controlled
blood pressure (mean systolic, 130 mm Hg) who stopped one
antihypertensive medication had similar rates of remaining at a systolic
blood pressure \textless{}150 mm Hg than people receiving usual
care.\textsuperscript{9} This flips the perceived value of deprescribing
on its head -- rather than having to show that deprescribing improves
clinical outcomes, in many settings it may be enough to say that people
can fare just as well stopping their medications than continuing them.
To be clear, we should not choose outcomes just because they are easy.
However, we should pursue opportunities where outcomes are both
clinically meaningful and have realistic potential to demonstrate
benefit -- or, where appropriate, non-inferiority - in response to
interventions.

\textbf{Recommendation \#4: Prioritize high-risk groups}

In many cases, deprescribing can be beneficial but has only small to
moderate effects on outcomes of interest. For example, deprescribing
fall-risk increasing drugs (FRIDs) may reduce the risk of falls -- yet
many other factors influence fall risk, so intervening solely on
medications will only go so far. In these settings, testing
deprescribing interventions in a population whose baseline risk of the
outcome is low almost guarantees that the study will be underpowered to
detect small to moderate (but still meaningful) effects.

We should thus test our interventions in populations who have high rates
of the outcome we seek to reduce, making it easier to detect a
beneficial effect for a given sample size. Consider an intervention that
reduces rates of a harmful outcome by one-third (i.e., relative risk
0.67). If the baseline outcome rate among participants in a controlled
clinical trial is 10\%, a sample size of more than 2300 people would be
required to detect the expected reduction from 10\% to 6.7\% (at P value
\textless{}0.05 and power of 0.80). In contrast, if 50\% of the
population has the outcome at baseline, fewer than 300 study subjects
would be required to detect the expected reduction in outcome rates.

\textbf{Recommendation \#5: Use out-of-the-box thinking}

An adage in quality improvement is that ``every system is designed to
achieve the result it gets.'' Why is deprescribing so challenging?
Because the health care system is constructed in a manner that foils
attempts to deprescribe in manifold ways. Tinkering around the edges of
this system is likely to do little good.

Rather, we are likely to have the greatest impact on deprescribing by
finding ways to bypass or step outside the system or to co-opt it for
our own benevolent ends. For example, changing clinician behavior is
notoriously difficult in many health systems. So, some of the most
interesting deprescribing interventions have come from bypassing the
system and most clinicians, bringing deprescribing messages and behavior
change strategies straight to patients.\textsuperscript{5} Or, given the
difficulty getting busy and overwhelmed clinicians to deprescribe, some
pioneers have created their own dedicated deprescribing clinics. There
is no single right answer, but in general we are likely to get more
traction by embracing innovative, non-traditional approaches that bypass
systems-level barriers than by butting up against them.

\textbf{Recommendation \#6: Be a secret agent}

Deprescribing is cohering as a professional identity. There are a number
of national and regional networks focused on this topic, and the first
international conference devoted to the topic was successfully convened
in September 2022. While these are positive developments, they come with
a danger of becoming insular. We must resist this temptation. Promoting
appropriate deprescribing is too large a task for deprescribing-focused
researchers and program leaders to take on alone, and the most impactful
changes will come by working with partners in a wide variety of research
fields and in health systems, guidelines, and governments. Our task is
to engage closely with these partners, understand their needs and
perspectives, and to bubble up opportunities to promote deprescribing
research within those environments aligned with the principles of
strategic science.\textsuperscript{10} Secret agents covertly
infiltrate; we can display our interests more openly but the principles
of building relationships, gaining trust, understanding people's
interests, and findings ways to align with those interests are
analogous.

\textbf{Conclusions}

As we envision the future of deprescribing research, paying careful
attention to how our work can be most relevant and impactful will be
critical to ensuring that the research we do makes a difference. The six
recommendations discussed in this commentary are hardly comprehensive --
for example, they do not address the importance of methodologic rigor --
but hopefully will stimulate thinking about how this small but mighty
field can successfully grow.

\textbf{Acknowledgements}

Acknowledgements:

The authors thanks Wade Thompson, Emily Reeve, and Cynthia Boyd for
their helpful suggestions on this manuscript and the lecture from which
it was derived.

Funding:

This work was supported by the National Institute on Aging (grants
R24AG064025 and K24AG049057)

Disclosures:

Dr. Steinman receives royalties from UpToDate and honoraria from the
American Geriatrics Society. This manuscript is based on a lecture given
at the First International Conference on Deprescribing (ICOD), Kolding,
Denmark, September 2022.

\textbf{Box: Recommendations for deprescribing research}

\begin{enumerate}
\tightlist
\item
  Keep doing the ``basic science'' of deprescribing and use it to inform
  interventions
\item
  Lean into behavior change -- or bypass it
\item
  Be strategic about outcomes
\item
  Prioritize high-risk groups
\item
  Use out-of-the-box thinking
\item
  Be a secret agent
\end{enumerate}



\textbf{References}

1. Reeve E. {[}Placeholder for Reeve article to be published in same
issue{]}. 2023.

2. Bloomfield HE, Greer N, Linsky AM, et al. Deprescribing for
Community-Dwelling Older Adults: a Systematic Review and
Meta-analysis.\emph{J Gen Intern Med.} 2020;35(11):3323-3332.

3. Kua CH, Mak VSL, Huey Lee SW. Health Outcomes of Deprescribing
Interventions Among Older Residents in Nursing Homes: A Systematic
Review and Meta-analysis. \emph{J Am Med Dir Assoc.} 2019;20(3):362-372
e311.

4. Thompson W, Reeve E, Moriarty F, et al. Deprescribing: Future
directions for research. \emph{Res Social Adm Pharm.}2019;15(6):801-805.

5. Tannenbaum C, Martin P, Tamblyn R, Benedetti A, Ahmed S. Reduction of
inappropriate benzodiazepine prescriptions among older adults through
direct patient education: the EMPOWER cluster randomized
trial.\emph{JAMA Intern Med.} 2014;174(6):890-898.

6. Steinman MA, Boyd CM, Spar MJ, Norton JD, Tannenbaum C. Deprescribing
and deimplementation: Time for transformative change. \emph{J Am Geriatr
Soc.} 2021.

7. McConeghy KW, Cinque M, White EM, et al. Lessons for deprescribing
from a nonessential medication hold policy in US nursing homes. \emph{J
Am Geriatr Soc.} 2022;70(2):429-438.

8. Ross JS, Frazee SG, Garavaglia SB, et al. Trends in use of ezetimibe
after the ENHANCE trial, 2007 through 2010. \emph{JAMA Intern
Med.}2014;174(9):1486-1493.

9. Sheppard JP, Burt J, Lown M, et al. Effect of Antihypertensive
Medication Reduction vs Usual Care on Short-term Blood Pressure Control
in Patients With Hypertension Aged 80 Years and Older: The OPTIMISE
Randomized Clinical Trial. \emph{JAMA.} 2020;323(20):2039-2051.

10. Brownell KD, Roberto CA. Strategic science with policy
impact.\emph{Lancet.} 2015;385(9986):2445-2446.

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