Evidence map›Paper›PMID 29599107›Full record

ArticleJournal of medical Internet research2018

Growth Dynamics of Patient-Provider Internet Communication: Trend Analysis Using the Health Information National Trends Survey (2003 to 2013).

Will L Tarver, Terri Menser, Bradford W Hesse, Tyler J Johnson, Ellen Beckjord, Eric W Ford, Timothy R Huerta

Abstract readHistorical Article
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  3. Leveraging large language models for generating responses to patient messages-a subjective analysis.Journal of the American Medical Informatics Association : JAMIA · 2024
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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

7 authors.

Will L TarverHealth Services Research and Development Service Center for Health Information and Communication, Richard L Roudebush VA Medical Center, Indianapolis, IN, United States.ORCID 0000-0001-7667-5758
Terri MenserCenter for Outcomes Research, Houston Methodist Research Institute, Houston, TX, United States.ORCID 0000-0003-3095-2590
Bradford W HesseHealth Communication and Informatics Research Branch, National Cancer Institute, Bethesda, MD, United States.ORCID 0000-0003-1142-1161
Tyler J JohnsonDepartment of Family Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0001-8746-9706
Ellen BeckjordPopulation Health Program Design and Engagement Optimization, UPMC Health Plan, Pittsburgh, PA, United States.ORCID 0000-0002-5291-2998
Eric W FordDepartment of Health Care Organization and Policy, University of Alabama at Birmingham, Birmingham, AL, United States.ORCID 0000-0002-7885-0019
Timothy R HuertaDepartment of Family Medicine, The Ohio State University, Columbus, OH, United States.ORCID 0000-0002-9978-3564

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunication is key in chronic disease management, and the internet has altered the manner in which patients and providers can exchange information. Adoption of secure messaging differs among patients due to the digital divide that keeps some populations from having effective access to online resources.

objectiveThis study aimed to examine the current state of online patient-provider communication, exploring trends over time in the use of online patient-provider communication tools.

methodsA 3-part analytic process was used to study the following: (1) reanalysis, (2) close replication across years, and (3) trend analysis extension. During the reanalysis stage, the publicly available Health Information National Trends Survey (HINTS) 1 and 2 data were used with the goal of identifying the precise analytic methodology used in a prior study, published in 2007. The original analysis was extended to add 3 additional data years (ie, 2008, 2011, and 2013) using the original analytical approach with the purpose of identifying trends over time. Multivariate logistic regression was used to analyze pooled data across all years, with year as an added predictor, in addition to a model for each individual data year.

resultsThe odds of internet users to communicate online with health care providers was significantly and increasingly higher year-over-year, starting in 2003 (2005: odds ratio [OR] 1.31, 95% CI 1.03-1.68; 2008: OR 2.14, 95% CI 1.76-2.59; 2011: OR 2.92, 95% CI 2.33-3.66; and 2013: OR 5.77; 95% CI 4.62-7.20). Statistically significant socio-economic factors found to be associated with internet users communicating online with providers included age, having health insurance, having a history of cancer, and living in an urban area of residence.

conclusionsThe proportion of internet users communicating online with their health care providers has significantly increased since 2003. Although these trends are encouraging, access challenges still exist for some groups, potentially giving rise to a new set of health disparities related to communication.

Indexed as

AdolescentAdultAgedChronic DiseaseCommunicationFemaleHistory, 21st CenturyHumansInternetMaleMedical InformaticsMiddle AgedSurveys and QuestionnairesYoung Adulthealth communicationinternet

Identifiers

PMID29599107
PMCPMC5897625

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.