Evidence map›Paper›PMID 42336175›Full record

ArticleApplied clinical informatics2026

Electronic Strategies for Tailored Exercise to Prevent Falls: Evaluating Implementation in Primary Care.

Jenna Reisler, Patricia Dykes, Nancy K Latham, Biai Digbeu, Efstathia Polychronopoulou, Michael Sainlaire, Tien Thai, Mackenzie Kiesman, Erin Hommel

Abstract read
In one paragraph

Article in Applied clinical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jenna ReislerThe University of Texas Medical Branch at Galveston, Texas, United States, Galveston.ORCID 0000-0001-8286-7318
Patricia DykesBrigham and Women's Hospital, Department of Medicine, General Internal Medicine, Massachusetts, United States, Boston.
Nancy K LathamBrigham and Women's Hospital, Massachusetts, United States, Boston.
Biai DigbeuThe University of Texas Medical Branch at Galveston, Texas, United States, Galveston.
Efstathia PolychronopoulouThe University of Texas Medical Branch at Galveston, Texas, United States, Galveston.
Michael SainlaireBrigham and Women's Hospital, Massachusetts, United States, Boston.
Tien ThaiBrigham and Women's Hospital, Department of Medicine, Massachusetts, United States, Boston.
Mackenzie KiesmanBrigham and Women's Hospital, Massachusetts, United States, Boston.
Erin HommelThe University of Texas Medical Branch at Galveston, Department of Medicine, Texas, United States, Galveston.

Funding

electronic Strategies for Tailored Exercise to Prevent FallS (eSTEPS).R61AG068926 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI DYKES, PATRICIA C, LATHAM, NANCY K · 2020 to 2021
$494k
NIA NIH HHS 1R61AG068926-01NIA NIH HHS R61 AG068926NIA NIH HHS R61AG068926
6 · The paper itself

Abstract

Background: Falls are the leading cause of injury and injury-related death among older adults. Clinical decision support (CDS) may improve clinician referral and patient access to fall prevention exercise. Objectives: We evaluated implementation of a CDS intervention linking high-risk older adults to gait and balance exercises and identified patient and clinician factors associated with success. Methods: Using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, we evaluated implementation year 1 after a 3-month wash-in period at clinics in an academic health system. Community-dwelling adults aged ≥ 65 seen in person by a physician or advanced practice provider were eligible. We implemented standardized fall risk screening, a CDS alert for positive screens, linked electronic order sets for gait and balance exercise, and preconfigured documentation text. We assessed reach, adoption, implementation, and maintenance; the primary outcome was connection to exercise via order sets or confirmed ongoing gait and balance exercise. Hierarchical logistic regression evaluated associations between patient and clinician characteristics and odds of this outcome. Results: The CDS alert reached 5,458 of 5,891 eligible patients (92.6%); 1,664 (30.5%) were connected to exercise. Male patient sex (odds ratio [OR]: 0.82; 95% confidence interval [CI]: 0.70-0.95) was associated with lower odds of connection, while multiple recent falls or a fall with injury increased odds (OR: 1.24; 95% CI: 1.02-1.49) compared with self-reported fear of falling. Variation in adoption by clinician was substantial (intraclass correlation coefficient approximately, 30%). No significant differences were found by patient age, race/ethnicity, or insurance, nor for clinician department or qualification. Conclusion: CDS can identify older adults at high fall risk and prompt referral to gait and balance exercise. However, adoption was modest and varied by clinician, with patient sex and recent fall history influencing uptake. Targeted strategies to improve clinician adoption and address patient biases may enhance implementation.

Indexed as

Accidental FallsExerciseExercise TherapyPrimary Health CareAgedAged, 80 and overDecision Support Systems, ClinicalFemaleHumansMale

Identifiers

PMID42336175
PMCPMC13400137

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.