ArticleJournal of medical Internet research2018
Characterization of Patient Interest in Provider-Based Consumer Health Information Technology: Survey Study.
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 16 papers.
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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.
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.
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Who cites it
16 citing papers in PubMed, 31 citations in OpenAlex.
- Digital Communication Technology: Does Offering a Choice of Modality Improve Medication Adherence and Outcomes in a Persistent Asthma Population?The Permanente journal · 2020Trial
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- Exploring the Acceptability of Text Messages to Inform and Support Shared Decision-making for Colorectal Cancer Screening: Online Panel Survey.JMIR cancer · 2023Article
- Digital Health Literacy in Patients With Heart Failure in Times of Pandemic.Computers, informatics, nursing : CIN · 2022Article
- Multidimensional Assessment of Individuals with Parkinson's Disease: Development and Structure Validation of a Self-Assessment Questionnaire.Healthcare (Basel, Switzerland) · 2022Article
- Clinical and translational research workforce education survey identifies needs of faculty and staff.Journal of clinical and translational science · 2022Article
- Estimating Patient Empowerment and Nurses' Use of Digital Strategies: eSurvey Study.International journal of environmental research and public health · 2021Article
- Goldilocks and the Three Bears: A Just-Right Hybrid Model to Synthesize the Growing Landscape of Publicly Available Health-Related Mobile Apps.Journal of medical Internet research · 2021Article
- The translational sciences clinic: From bench to bedside.Journal of clinical and translational science · 2020Article
- Engaging hematopoietic cell transplantation patients and caregivers in the design of print and mobile application individualized survivorship care plan tools.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2020Article
- Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire.European radiology · 2020Article
- An institution-wide faculty mentoring program at an academic health center with 6-year prospective outcome data.Journal of clinical and translational science · 2019Article
- Providing Access: Differences in Pediatric Portal Activation Begin at Patient Check-in.Applied clinical informatics · 2019Article
- Determinants of mobile technology use and smartphone application interest in cancer patients.Cancer medicine · 2018Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundConsumer health information technology can improve patient engagement in their health care and assist in navigating the complexities of health care delivery. However, the consumer health information technology offerings of health systems are often driven by provider rather than patient perspectives and inadequately address patient needs, thus limiting their adoption by patients. Consideration given to patients as stakeholders in the development of such technologies may improve adoption, efficacy, and consumer health information technology resource allocation.
objectiveThe aims of this paper were to measure patient interest in different health system consumer health information technology apps and determine the influence of patient characteristics on consumer health information technology interest.
methodsPatients seen at the Cleveland Clinic Neurological Institute were electronically surveyed on their interest in using different consumer health information technology apps. A self-efficacy scale, Patient Health Questionnaire-9 depression screen, and EuroQol 5 dimensions health-related quality of life scale were also completed by patients. Logistic regression was used to determine the influence of patient characteristics on interest in consumer health information technology in the categories of self-management, education, and communication.
resultsThe majority of 3852 patient respondents had an interest in all technology categories assessed in the survey. The highest interest was in apps that allow patients to ask questions of providers (3476/3852, 90.24%) and to schedule appointments (3211/3839, 83.64%). Patient interest in consumer health information technology was significantly associated with greater depression symptoms, worse quality of life, greater health self-efficacy, and smartphone ownership (P<.001 for all listed).
conclusionsPatients should be viewed as active stakeholders in consumer health information technology development and their perspectives should consistently guide development efforts. Health systems should consider focusing on consumer health information technologies that assist patients in scheduling appointments and asking questions of providers. Patients with depression should also be considered for targeted consumer health information technology implementation. Health self-efficacy is a valid predictor of consumer health information technology interest and may play a role in the utilization of consumer health information technologies. Health systems, broadly, should put forth greater effort to understand the needs and interests of patients in the consumer health information technology development process. Consumer health information technology design and implementation may be improved by understanding which technologies patients want.
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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.