Evidence map›Paper›PMID 40772787›Full record

ArticleJournal of medical Internet research2025

Impact of Initial Cardiology Telemedicine Evaluation on Follow-Up Visits for Common Conditions: Quasi-Experimental Study.

Neil M Kalwani, Harrison Koos, Emily Kohn, Vijaya Parameswaran, Anica Oesterle, Marina Adrianzen, Febri Kurniawan, Lubna Qureshi, Rajesh Dash, Paul Heidenreich and 2 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. 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

12 authors.

Neil M Kalwani *Cardiology Section, Medical Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Cardiology (111C), Palo Alto, CA, 94304, United States, 1 6504935000.ORCID http://orcid.org/0000-0003-0075-6206
Harrison Koos *Department of Health Policy, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0003-3051-5948
Emily KohnDepartment of Management Science and Engineering, School of Engineering, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0002-8540-6311
Vijaya ParameswaranDivision of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0002-0984-9938
Anica OesterleDepartment of Management Science and Engineering, School of Engineering, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0009-0000-0003-9464
Marina AdrianzenDepartment of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, WI, United States.ORCID http://orcid.org/0009-0002-1849-6190
Febri KurniawanStanford Prevention Research Center, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0009-0004-6487-4425
Lubna QureshiStanford Health Care, Palo Alto, CA, United States.ORCID http://orcid.org/0009-0009-9365-4014
Rajesh DashDivision of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0002-2499-6389
Paul HeidenreichCardiology Section, Medical Service, VA Palo Alto Health Care System, 3801 Miranda Avenue, Cardiology (111C), Palo Alto, CA, 94304, United States, 1 6504935000.ORCID http://orcid.org/0000-0001-7730-8490
David ScheinkerDivision of Pediatric Endocrinology & Diabetes, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0001-5885-8024
Fatima RodriguezDivision of Cardiovascular Medicine and the Cardiovascular Institute, School of Medicine, Stanford University, Stanford, CA, United States.ORCID http://orcid.org/0000-0002-5226-0723

Funding

Opportunistic Atherosclerotic Cardiovascular Disease Risk Estimation at Abdominal CTs with Robust and Unbiased Deep LearningR01HL167974 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2023 to 2026
$2.4M
Novel Incidental Calcium Evaluation (NICE)R01HL169345 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2024 to 2026
$2.1M
Adherence Determinants in the Health Electronic Record Evaluation of Statins (ADHERES)R01HL168188 · NHLBI · STANFORD UNIVERSITY · PI Fatima Rodriguez · 2024 to 2026
$2.1M
AHRQ HHS T32 HS026128NHLBI NIH HHS R01 HL167974NHLBI NIH HHS R01 HL168188NHLBI NIH HHS R01 HL169345
6 · The paper itself

Abstract

Background: Telemedicine use has increased significantly in cardiology clinics, but the impact of initial telemedicine evaluation on total visit usage is unknown. Objective: This study aimed to determine the effect of initial telemedicine evaluation on the number of follow-up visits within 6 months for common cardiovascular conditions at an academic health system. Methods: Electronic health records data were extracted for general cardiology visits. New patient visits (NPVs) were included occurring from June 1, 2020, to May 31, 2023, for 10 common cardiovascular conditions-atrial fibrillation or flutter, chest pain, coronary artery disease, dyslipidemia, dyspnea, heart failure, hypertension, palpitations, preoperative evaluation, and syncope or dizziness. The effect of initial telemedicine versus in-person evaluation on follow-up visits within 6 months was assessed using a 2-stage least squares instrumental variable model with the proportion of clinician telemedicine use as the instrument and adjustment for patient and visit characteristics. Results: There were 5528 NPVs conducted by 40 general cardiology clinicians during the study period. The average patient age was 56 (SD 17.5) years, 54.2% (2998/5528) were female, 43.2% (2389/5528) were non-Hispanic White, 24.7% (1368/5528) were Asian, 13.8% (761/5528) were Hispanic, 34.4% (1904/5528) were on Medicare, and 13.2% (729/5528) were on Medicaid. Of the NPVs, 53.5% (2959/5528) were conducted via telemedicine (2814/5528, 50.9% via video and 145/5528, 2.6% via phone). Telemedicine use for NPVs ranged from 0% to 100% (N=40) across individual clinicians. The average number of follow-up visits was 57 visits per 100 patients within 6 months across all diagnosis groups. Patients receiving telemedicine NPVs were more likely to have telemedicine follow-up visits than those receiving in-person NPVs (1354/1619, 83.6% vs 680/1533, 44.4%). In the instrumental variable analysis, the impact of initial telemedicine evaluation differed by presenting condition. There was an increase in follow-up visits for patients with syncope or dizziness (29.8 visits/100 patients, 95% CI 6.4-53.1), palpitations (34.9 visits/100 patients, 95% CI 18.6-51.1), chest pain (36.9 visits/100 patients, 95% CI 18.5-55.2), and dyspnea (37.0 visits/100 patients, 95% CI 11.8-62.0). There was a decrease in follow-up visits for patients with coronary artery disease (-29.5 visits/100 patients, 95% CI -50.3 to -8.6) and dyslipidemia (-24.5 visits/100 patients, 95% CI -40.2 to -8.8). There was no significant effect for patients presenting for atrial fibrillation or flutter, heart failure, hypertension, and preoperative evaluation. Conclusions: The effect of initial telemedicine evaluation on follow-up visits varied significantly by presenting condition in this cardiology practice. Telemedicine use resulted in increased follow-up visits for patients presenting with symptomatic complaints, while for those presenting with chronic conditions, there was no significant effect or a decrease in visits. Future studies should assess strategies to target initial care modalities to appropriate patients in cardiology clinics with early in-person evaluation for symptomatic patients.

Indexed as

CardiologyCardiovascular DiseasesTelemedicineAdultAgedElectronic Health RecordsFemaleFollow-Up StudiesHumansMaleMiddle Agedambulatory carecardiologycardiovascular diseasechronic diseasehealth care deliveryhealth care utilizationsymptom assessmenttelemedicine

Identifiers

PMID40772787
PMCPMC12330163

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Registered trials

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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.