# Optimizing electronic health record prompts with behavioral economics to improve prescribing for older adults

> **NIH NIH R33** · BRIGHAM AND WOMEN'S HOSPITAL · 2020 · $791,657

## Abstract

Prescribing of potentially unsafe medications for older adults is extremely common; benzodiazepines,
antipsychotics, anticholinergics, and sedative hypnotics are four key drug classes frequently implicated in
adverse health consequences for vulnerable older adults, such as confusion or sedation, leading to
hospitalizations, falls, and fractures. Fortunately, most of these consequences are preventable. Physicians’
lack of awareness of alternatives, ambiguous practice guidelines, and perceived pressure from patients or
caregivers are among the reasons why these drugs are used more than might be optimal. Reducing
inappropriate use of these drugs may be achieved through decision support tools for providers that are
embedded in electronic health record (EHR) systems. While EHR strategies are widely used to support the
informational needs of providers, these tools have demonstrated only modest effectiveness at improving
prescribing. The effectiveness of these tools could be enhanced by leveraging principles of behavioral
economics and related sciences. In specific, three behavioral economic principles, such as salience effects,
social norming, and default bias, have successfully changed behavior in other settings but have had very
limited application in EHRs and, more specifically, for prescribing in older adults.
 To this end, we propose three cluster randomized controlled trials of novel EHR decision support tools that
seek to reduce inappropriate prescribing for these drug classes and their associated adverse drug events and
health outcomes. This proposal builds on many years of research by our group on interventions to engage
providers and patients in clinical-decision making, behavior change, and evaluating novel interventions in real-
world delivery systems. The EHR decision support tools will be designed using promising behavioral economic
principles such as salience effects, social norming, and default bias.
 The specific aims of this study are to: (1) design and pilot test multiple EHR decision support tools
constructed using behavioral economics principles; (2) rapidly identify the potential effectiveness of numerous
EHR tools at reducing inappropriate prescribing using a novel randomized adaptive design; (3) examine
whether these most potentially promising EHR tools from Aim 2 reduce inappropriate prescribing and adverse
drug events when using a randomized parallel group trial; and (4) evaluate the effectiveness of the EHR tools
in a different clinical environment. Using rigorous randomized designs, we have proposed a pragmatic and
scalable approach to optimizing and evaluating EHR tools aimed at provider behavior change for prescribing
for older adults. We will also be able to rigorously test a large number of EHR tools as well as replicate and
validate the effectiveness of the best performing tools in a different healthcare system. The expected overall
impact of this innovative proposal is that it will fundamentally advance how behavioral ...

## Key facts

- **NIH application ID:** 10017795
- **Project number:** 5R33AG057388-04
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Niteesh K Choudhry
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $791,657
- **Award type:** 5
- **Project period:** 2017-09-15 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017795

## Citation

> US National Institutes of Health, RePORTER application 10017795, Optimizing electronic health record prompts with behavioral economics to improve prescribing for older adults (5R33AG057388-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10017795. Licensed CC0.

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