Characterization of Patient Interest in Provider-Based Consumer Health Information Technology: Survey Study
- PMID: 29674312
- PMCID: PMC6004033
- DOI: 10.2196/jmir.7766
Characterization of Patient Interest in Provider-Based Consumer Health Information Technology: Survey Study
Abstract
Background: Consumer 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.
Objective: The 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.
Methods: Patients 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.
Results: The 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).
Conclusions: Patients 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.
Keywords: consumer health informatics; medical informatics; patient-centered care; self efficacy; self-management; telemedicine.
©Joseph Featherall, Brittany Lapin, Alexander Chaitoff, Sonia A Havele, Nicolas Thompson, Irene Katzan. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.04.2018.
Conflict of interest statement
Conflicts of Interest: None declared.
Figures

Similar articles
-
Connected health: a review of technologies and strategies to improve patient care with telemedicine and telehealth.Health Aff (Millwood). 2014 Feb;33(2):194-9. doi: 10.1377/hlthaff.2013.0992. Health Aff (Millwood). 2014. PMID: 24493760 Review.
-
Preferences for Health Information Technologies Among US Adults: Analysis of the Health Information National Trends Survey.J Med Internet Res. 2018 Oct 18;20(10):e277. doi: 10.2196/jmir.9436. J Med Internet Res. 2018. PMID: 30341048 Free PMC article.
-
[Consumer health-care information technology].Gesundheitswesen. 2013 Jun;75(6):400-2. doi: 10.1055/s-0033-1343445. Epub 2013 May 21. Gesundheitswesen. 2013. PMID: 23695812 German.
-
How Can eHealth Technology Address Challenges Related to Multimorbidity? Perspectives from Patients with Multiple Chronic Conditions.J Gen Intern Med. 2015 Aug;30(8):1063-70. doi: 10.1007/s11606-015-3222-9. Epub 2015 Feb 18. J Gen Intern Med. 2015. PMID: 25691239 Free PMC article.
-
A review of user-centered design for diabetes-related consumer health informatics technologies.J Diabetes Sci Technol. 2013 Jul 1;7(4):1039-56. doi: 10.1177/193229681300700429. J Diabetes Sci Technol. 2013. PMID: 23911188 Free PMC article. Review.
Cited by
-
Determinants of mobile technology use and smartphone application interest in cancer patients.Cancer Med. 2018 Nov;7(11):5812-5819. doi: 10.1002/cam4.1660. Epub 2018 Oct 2. Cancer Med. 2018. PMID: 30280495 Free PMC article.
-
Multidimensional Assessment of Individuals with Parkinson's Disease: Development and Structure Validation of a Self-Assessment Questionnaire.Healthcare (Basel). 2022 Sep 21;10(10):1823. doi: 10.3390/healthcare10101823. Healthcare (Basel). 2022. PMID: 36292272 Free PMC article.
-
The Use of Technology Platforms for Nutrition Education in Cirrhosis: A Cross-Sectional Study of Patients' Acceptability and Capabilities.Can Liver J. 2025 Mar 27;8(2):309-321. doi: 10.3138/canlivj-2024-0058. eCollection 2025 May. Can Liver J. 2025. PMID: 40677982 Free PMC article.
-
Estimating Patient Empowerment and Nurses' Use of Digital Strategies: eSurvey Study.Int J Environ Res Public Health. 2021 Sep 18;18(18):9844. doi: 10.3390/ijerph18189844. Int J Environ Res Public Health. 2021. PMID: 34574766 Free PMC article.
-
The translational sciences clinic: From bench to bedside.J Clin Transl Sci. 2020 Aug 25;5(1):e36. doi: 10.1017/cts.2020.529. J Clin Transl Sci. 2020. PMID: 33948258 Free PMC article.
References
-
- Berwick DM, Nolan TW, Whittington J. The triple aim: care, health, and cost. Health Aff (Millwood) 2008;27(3):759–69. doi: 10.1377/hlthaff.27.3.759. http://content.healthaffairs.org/cgi/pmidlookup?view=long&pmid=18474969 27/3/759 - DOI - PubMed
-
- Sheikh A, Sood HS, Bates DW. Leveraging health information technology to achieve the “triple aim” of healthcare reform. J Am Med Inform Assoc. 2015 Jul;22(4):849–56. doi: 10.1093/jamia/ocv022. http://europepmc.org/abstract/MED/25882032 ocv022 - DOI - PMC - PubMed
-
- Or CK, Karsh B. A systematic review of patient acceptance of consumer health information technology. J Am Med Inform Assoc. 2009 Aug;16(4):550–60. doi: 10.1197/jamia.M2888. http://jamia.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=19390112 M2888 - DOI - PMC - PubMed
-
- Improving Consumer Health IT Application Development: Lessons From Other Industries https://healthit.ahrq.gov/sites/default/files/docs/citation/background_r... .
-
- Eysenbach G. Consumer health informatics. Br Med J. 2000 Jun 24;320(7251):1713–6. http://europepmc.org/abstract/MED/10864552 - PMC - PubMed
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical