# Can EHR Alerts Prevent Falls in Older Adults? > Can EHR alerts prevent falls in older adults? eSTEPS found a modestly lower coded-fall rate with exercise guidance; see what clinics should track and the study’s limits. ![Can EHR Alerts Prevent Falls in Older Adults?](https://longevity.nicheflash.com/media/articles/2738-3c21hc4kgzg4-16x9.jpg) - Source: https://longevity.nicheflash.com/blogs/can-electronic-health-record-alerts-prevent-falls-older-adults - Author: [Longevity Blogs Editorial Team](https://longevity.nicheflash.com/authors/longevity-blogs-editorial-team) - Publisher: Longevity Blogs - Published: 2026-10-18 - Updated: 2026-10-18 **Key takeaways** - An EHR alert linked to exercise guidance may help reduce coded fall rates, but the eSTEPS trial tested a program—not an alert on its own. [1] - The intervention group had 1.9 fewer coded falls per 100 patient-years than the control group, a group-level event-rate difference rather than an individual prediction. [1] - In intervention practices, 77.9% of clinicians used the decision support at least once, while 22.1% of intervention patients received an exercise prescription. [1] - The trial took place in 22 practices in one health system, and reliance on diagnostic codes may have missed falls. [1] Can electronic health record alerts prevent falls in older adults? The eSTEPS trial suggests that an EHR-integrated fall-prevention program can modestly lower the rate of coded falls. It does not show that an alert alone prevents falls or that every patient will benefit. [1] ## What did the eSTEPS fall-prevention alert do? eSTEPS linked fall-risk screening in primary care with tailored strength and balance exercise guidance. Its clinical decision support appeared as a noninterruptive care-gap alert in the Epic EHR. An accompanying order set offered exercise recommendations and patient-facing resources. [1] The cluster randomized trial enrolled adults aged 65 or older who screened positive for fall risk at 22 primary-care practices in one integrated US health system. The trial ran from June 9, 2023, to May 8, 2025, and follow-up lasted 12 to 23 months. These are the trial and follow-up dates, not the date the results were published. [1] Practices were assigned to intervention or control groups. Because the intervention combined EHR decision support, exercise guidance, and patient resources, the results assess that program as delivered—not the effect of a prompt in isolation. [1] ## How much did the alert change fall rates? Among 11,945 participants, coded falls occurred at a rate of 19.3 per 100 patient-years in intervention practices (95% CI, 18.6-20.1), compared with 21.2 per 100 patient-years in control practices (95% CI, 20.2-22.1). [1] The difference was 1.9 fewer coded falls per 100 patient-years in the intervention group. That is a group-level difference in the rate of recorded fall events over person-time. It should not be read as two fewer people falling per 100 people, or as a prediction for an individual patient. [1] The fall rate ratio was 0.91 (95% CI, 0.88-0.95; P < .001), indicating a statistically significant but modest difference between the trial groups. [1] Coded fall-related injuries occurred at a rate of 15.7 per 100 patient-years in intervention practices (95% CI, 15.0-16.5) and 16.7 in control practices (95% CI, 16.1-17.4). The paper reported no observed difference in mortality. [1] ## Did the alert reach patients and clinicians in routine care? The two reported uptake figures measure different things. In intervention practices, 77.9% of clinicians used the decision support at least once during the study; 22.1% of intervention patients received an exercise prescription. The clinician figure is not the share of patients reached, and a prescription does not show that a patient completed the exercises. [1] 1. **Eligibility:** Adults aged 65 or older screened positive for fall risk. [1] 2. **Prompt:** A noninterruptive care-gap alert appeared in the Epic EHR. [1] 3. **Offer:** An order set presented tailored strength and balance exercise recommendations and patient resources. [1] 4. **Uptake:** Clinicians used the tool at least once, and some intervention patients received exercise prescriptions; these are separate measures of implementation. [1] 5. **Outcome:** Intervention practices had a lower coded fall rate, but the trial does not establish that every eligible patient received or completed the exercise plan. [1] ## What are the important limits of the eSTEPS result? The primary outcome relied on EHR diagnostic codes, so falls that were not recorded may have been missed. The researchers cautioned that this could have led to an underestimate of fall frequency. [1] The study involved 22 practices in one integrated US health system. Results may not transfer unchanged to other health systems, workflows, or EHR platforms. The group-level findings also do not guarantee an individual outcome, and the trial did not isolate the alert from the rest of the intervention. [1] ## How does the trial fit existing fall-prevention guidance? eSTEPS tested one way to place exercise guidance into a primary-care workflow; it did not introduce a new recommendation about exercise. The U.S. Preventive Services Task Force (USPSTF) recommends exercise interventions for community-dwelling adults aged 65 or older who are at increased risk for falls (Grade B). [1][2] For the same population, the USPSTF recommends individualizing the decision to offer multifactorial interventions (Grade C). In practice, this means exercise has an affirmative recommendation, while the decision about a multifactorial approach should reflect the person and circumstances. [2] The CDC’s STEADI program describes its core elements as “Screening, assessing, and intervening” and provides healthcare providers with coordinated care and evaluation plans for fall-prevention programs in primary care. [3] Clinics considering an EHR alert can use this checklist: - Confirm which patients qualify for fall-risk screening. - Assign responsibility for reviewing the alert and offering the exercise plan. - Track the share of eligible patients who receive a prescription after an alert, and the share of prescribed patients who complete the plan. - Compare locally recorded fall outcomes over time, while noting that diagnostic codes may miss falls. These measures help clinics assess whether the workflow fits their screening, referral, and follow-up processes without assuming that eSTEPS results will automatically reproduce locally. [1][3] ## Frequently asked questions ### Does eSTEPS show that every patient who received an exercise prescription avoided a fall? No. The trial compared group outcomes, and falls continued to occur in both groups. It did not guarantee an individual result or report that every patient completed the exercises. [1] ### Can a clinic using an EHR other than Epic expect the same result? The trial tested a workflow embedded in Epic at practices within one integrated US health system. It does not establish that the same result will occur on other platforms or in other settings. [1] ### Did eSTEPS show that the intervention reduced fall-related deaths? No. The paper reported no observed difference in mortality. [1] ### How does the USPSTF’s multifactorial recommendation differ from its exercise recommendation? The USPSTF recommends exercise interventions for community-dwelling adults aged 65 or older at increased risk for falls (Grade B). For multifactorial interventions, it recommends that clinicians individualize the decision to offer them (Grade C). [2] ## References 1. “Clinical Decision Support for Fall Prevention in Primary Care: The eSTEPS Cluster Randomized Clinical Trial.” Results publication date: October 16, 2026. The trial dates were June 9, 2023, to May 8, 2025. [1] 2. U.S. Preventive Services Task Force. Recommendation statement on interventions to prevent falls in community-dwelling older adults, including exercise interventions and multifactorial interventions. [2] 3. Centers for Disease Control and Prevention. STEADI (Stopping Elderly Accidents, Deaths & Injuries) program resources for fall prevention in primary care. [3] ## References 1. [jamanetwork.com](https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2855390) 2. [uspreventiveservicestaskforce.org](https://www.uspreventiveservicestaskforce.org/uspstf/index.php/recommendation/falls-prevention-community-dwelling-older-adults-interventions) 3. [cdc.gov](https://www.cdc.gov/steadi/hcp/clinical-resources/outpatient-care.html)