The Added Value of Log File Analyses of the Use of a Personal Health Record for Patients With Type 2 Diabetes Mellitus: Preliminary Results
Open accessAbstract
Background: The electronic personal health record (PHR) is a promising technology for improving the quality of chronic disease management. Until now, evaluations of such systems have provided only little insight into why a particular outcome occurred. The aim of this study is to gain insight into the navigation process (what functionalities are used, and in what sequence) of e-Vita, a PHR for patients with type 2 diabetes mellitus (T2DM), to increase the efficiency of the system and improve the long-term adherence. Method: Log data of the first visits in the first 6 weeks after the release of a renewed version of e-Vita were analyzed to identify the usage patterns that emerge when users explore a new application. Results: After receiving the invitation, 28% of all registered users visited e-Vita. In total, 70 unique usage patterns could be identified. When users visited the education service first, 93% of all users ended their session. Most users visited either 1 or 5 or more services during their first session, but the distribution of the routes was diffuse. Conclusions: In conclusion, log file analyses can provide valuable prompts for improving the system design of a PHR. In this way, the match between the system and its users and the long-term adherence has the potential to increase.
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In a previous study, users of a personal health record followed the global menu structure when exploring the PHR for the first time, and most users were likely to drop out when they visited the education section as a first step after the first login.
“For example, in a previous study we found that users of a personal health record (PHR), an electronic application consisting of different tools for monitoring and coaching patients with chronic conditions to support self-management [22], followed the global menu structure when exploring the PHR for the first time. Furthermore, most users were likely to drop out when they visited the education sect”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [23]
Users followed the structure of the system in first visits to the PHR for patients with chronic conditions.
“The results showed that users followed the structure of the system.”
From Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data (2017) · cites this paper as [23]
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Cites
Global estimates of the prevalence of diabetes for 2010 and 2030
Shaw, J. E., Sicree, R. A., & Zimmet, P. Z. (2010) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2009.10.007 · Cited by 7,216 · see citing works
Patient Self-management of Chronic Disease in Primary Care
Bodenheimer, T. (2002) · JAMA · doi:10.1001/jama.288.19.2469 · Cited by 3,598 · cited 3× · see citing works
“(4) Self-monitoring personal health values, where users can register the values they measured for blood pressure, waist circumference, weight, and BMI.”
BackgroundMethodEysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524 · see citing works
The Impact of eHealth on the Quality and Safety of Health Care: A Systematic Overview
Black, A. D., Car, J., Pagliari, C., Anandan, C., Cresswell, K., Bokun, T., McKinstry, B., Procter, R., Majeed, A., & Sheikh, A. (2011) · PLoS Medicine · doi:10.1371/journal.pmed.1000387 · Cited by 1,442 · see citing works
Personal Health Records: Definitions, Benefits, and Strategies for Overcoming Barriers to Adoption
Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., & Sands, D. Z. (2005) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2025 · Cited by 1,424 · see citing works
A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies
van Gemert-Pijnen, J. E., Nijland, N., van Limburg, M., Ossebaard, H. C., Kelders, S. M., Eysenbach, G., & Seydel, E. R. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1672 · Cited by 1,126 · see citing works
Self-citationQuality Improvement in Chronic Illness Care: A Collaborative Approach
Wagner, E. H., Glasgow, R. E., Davis, C., Bonomi, A. E., Provost, L., McCulloch, D., Carver, P., & Sixta, C. (2001) · The Joint Commission Journal on Quality Improvement · doi:10.1016/s1070-3241(01)27007-2 · Cited by 726 · see citing works
Kaplan, B. (2001) · International Journal of Medical Informatics · doi:10.1016/s1386-5056(01)00184-8 · Cited by 380 · see citing works
Potential of electronic personal health records
Pagliari, C., Detmer, D. E., & Singleton, P. (2007) · BMJ · doi:10.1136/bmj.39279.482963.ad · Cited by 306 · see citing works
Asynchronous and synchronous teleconsultation for diabetes care: A systematic literature review
Verhoeven, F., Tanja-Dijkstra, K., Nijland, N., Eysenbach, G., & van Gemert-Pijnen, L. (2010) · Journal of Diabetes Science and Technology · doi:10.1177/193229681000400323 · Cited by 247 · see citing works
Nijland, N., van Gemert-Pijnen, J. E., Kelders, S. M., Brandenburg, B. J., & Seydel, E. R. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1603 · Cited by 175 · see citing works
Self-citationPatient Web Portals to Improve Diabetes Outcomes: A Systematic Review
Osborn, C. Y., Mayberry, L. S., Mulvaney, S. A., & Hess, R. (2010) · Current Diabetes Reports · doi:10.1007/s11892-010-0151-1 · Cited by 175 · see citing works
The Association Between Personal Health Record Use and Diabetes Quality Measures
Tenforde, M. W., Nowacki, A. S., Jain, A., & Hickner, J. M. (2011) · Journal of General Internal Medicine · doi:10.1007/s11606-011-1889-0 · Cited by 121 · see citing works
Kelders, S. M., Bohlmeijer, E. T., & Van Gemert-Pijnen, J. E. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2258 · Cited by 88 · see citing works
Self-citationUsing Telemedicine to Improve Outcomes in Diabetes—An Emerging Technology
Klonoff, D. C. (2009) · Journal of Diabetes Science and Technology · doi:10.1177/193229680900300401 · Cited by 85 · see citing works
The value of personal health records for chronic disease management: what do we know?
Tenforde, M. W., Jain, A., & Hickner, J. M. (2011) · PubMed · Cited by 80 · see citing works
(2002) · American Journal of Preventive Medicine · doi:10.1016/s0749-3797(02)00422-1 · Cited by 76 · see citing works
Using an Internet Comanagement Module to Improve the Quality of Chronic Disease Care
Goldberg, H. I., Ralston, J. D., Hirsch, I. B., Hoath, J. I., & Ahmed, K. I. (2003) · The Joint Commission Journal on Quality and Safety · doi:10.1016/s1549-3741(03)29053-5 · Cited by 68 · see citing works
Telemedicine and Diabetes Management: Current Challenges and Future Research Directions
Bellazzi, R. (2008) · Journal of Diabetes Science and Technology · doi:10.1177/193229680800200114 · Cited by 49 · see citing works
Transaction logfile analysis in health communication research: Challenges and opportunities
Han, J. Y. (2011) · Patient Education and Counseling · doi:10.1016/j.pec.2010.12.018 · Cited by 31 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Pham, Q., Graham, G., Carrion, C., Morita, P. P., Seto, E., Stinson, J. N., & Cafazzo, J. A. (2019) · JMIR mHealth and uHealth · doi:10.2196/11941 · Cited by 131 · see citing works
Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data
Sieverink, F., Kelders, S., Poel, M., & van Gemert-Pijnen, L. (2017) · JMIR Research Protocols · doi:10.2196/resprot.6452 · Cited by 88 · see citing works
Self-citationPatient Portal Use in Diabetes Management: Literature Review
Sun, R., Korytkowski, M. T., Sereika, S. M., Saul, M. I., Li, D., & Burke, L. E. (2018) · JMIR Diabetes · doi:10.2196/11199 · Cited by 54 · see citing works
Talboom-Kamp, E. P. W. A., Verdijk, N. A., Kasteleyn, M. J., Harmans, L. M., Talboom, I. J. S. H., Numans, M. E., & Chavannes, N. H. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7037 · Cited by 33 · see citing works
Fraccaro, P., Vigo, M., Balatsoukas, P., Buchan, I. E., Peek, N. B., & van der Veer, S. N. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.12.028 · Cited by 31 · see citing works
Metrics for Outpatient Portal Use Based on Log File Analysis: Algorithm Development
Tosto, G. D., McAlearney, A. S., Fareed, N., & Huerta, T. R. (2020) · Journal of Medical Internet Research · doi:10.2196/16849 · Cited by 25 · see citing works
Scheckel, B., Schmidt, K., Stock, S., & Redaèlli, M. (2023) · Journal of Medical Internet Research · doi:10.2196/38447 · Cited by 25 · see citing works
Patient Engagement as Measured by Inpatient Portal Use: Methodology for Log File Analysis
Huerta, T. R., Fareed, N., Hefner, J. L., Sieck, C. J., Swoboda, C. M., Taylor, R. M., & McAlearney, A. S. (2018) · Journal of Medical Internet Research · doi:10.2196/10957 · Cited by 25 · see citing works
Loohuis, A. M. M., Wessels, N. J., Jellema, P., Vermeulen, K. M., Hove, M. C. P. S., van Gemert‐Pijnen, J. E. W. C., Berger, M. Y., Dekker, J. H., & Blanker, M. H. (2018) · Neurourology and Urodynamics · doi:10.1002/nau.23507 · Cited by 24 · see citing works
van Gemert-Pijnen, L. (. E. W. C. )., Kelders, S. M., Jong, N. B.-D., & B, H. O.-K. A. (2018) · Routledge eBooks · doi:10.4324/9781315385907-11 · Cited by 23 · see citing works
Self-citationHow Cancer Patients Use and Benefit from an Interactive Cancer Communication System
Han, J. Y., Hawkins, R. P., Baker, T. B., Shah, D. V., Pingree, S., & Gustafson, D. H. (2017) · Journal of Health Communication · doi:10.1080/10810730.2017.1360413 · Cited by 20 · see citing works
Inpatient portal clusters: identifying user groups based on portal features
Fareed, N., Walker, D. M., Sieck, C. J., Taylor, R. M., Scarborough, S., Huerta, T. R., & McAlearney, A. S. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy147 · Cited by 18 · see citing works
Talboom-Kamp, E. P. W. A., Holstege, M. S., Chavannes, N. H., & Kasteleyn, M. J. (2019) · Respiratory Research · doi:10.1186/s12931-019-1110-2 · Cited by 18 · see citing works
du Pon, E., Kleefstra, N., Cleveringa, F. G. W., van Dooren, A. A., Heerdink, E. R., & van Dulmen, S. (2020) · Journal of Diabetes Research · doi:10.1155/2020/5013142 · Cited by 17 · see citing works
Paydar, S., Emami, H., Asadi, F., Moghaddasi, H., & Hosseini, A. (2021) · PubMed Central · Cited by 16 · see citing works
Roelofsen, Y., van Vugt, M., Hendriks, S. H., van Hateren, K. J. J., Groenier, K. H., Snoek, F. J., Kleefstra, N., Huijsman, R., & Bilo, H. J. G. (2015) · Journal of Diabetes Research · doi:10.1155/2016/6343927 · Cited by 7 · see citing works
CeHRes Roadmap to Improve Dementia Care
van Gemert-Pijnen, L., & Span, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-01583-5_15 · Cited by 7 · see citing works
Peran Personal Health Record (PHR) dalam Pengelolaan Diabetes Melitus Tipe 2
Srimayarti, B. N., Siregar, K. N., & Rahmaniati, M. (2019) · Jurnal Manajemen Kesehatan Yayasan RS Dr Soetomo · doi:10.29241/jmk.v5i1.150 · Cited by 6 · see citing works
Evaluating a Strengths-Based mHealth Tool (MyStrengths): Explorative Feasibility Trial
Jessen, S., Mirković, J., Brendmo, E. H., & Nes, L. S. (2021) · JMIR Formative Research · doi:10.2196/30572 · Cited by 6 · see citing works
The Diffusion of a Personal Health Record for Patients with Type 2 Diabetes Mellitus in Primary Care
Sieverink, F., Braakman‐Jansen, L. M. A., Roelofsen, Y., Hendriks, S. H., Sanderman, R., Bilo, H. J. G., & van Gemert‐Pijnen, J. E. W. C. (2014) · Cited by 6 · see citing works
Self-citationCeHRes Roadmap to Improve Dementia Care
van Gemert-Pijnen, L., & Span, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-01904-8_15-2 · Cited by 5 · see citing works
Sieverink, F. (2017) · doi:10.3990/1.9789036544177 · Cited by 5 · see citing works
Self-citationten Klooster, I., Noordzij, M. L., & Kelders, S. M. (2019) · JMIR Human Factors · doi:10.2196/14424 · Cited by 4 · see citing works
Self-citationSieverink, F., Kelders, S. M., Akkersdijk, S. M., Poel, M., Siemons, L., & van Gemert‐Pijnen, J. E. W. C. (2016) · University of Twente Research Information · Cited by 3 · see citing works
Self-citationvan Schalkwyk, A., Grobbelaar, S. S. S., Vermeulen, E., & Herselman, M. E. (2022) · IEEE Access · doi:10.1109/access.2022.3224038 · Cited by 2 · see citing works
Mobile Application Development for Diabetes Patient
Potyok, C., Simon, B. F., Hartvég, Á., Siket, M., Dénes-Fazakas, L., Eigner, G., Balázs, M., Kovács, L., & Szilágyi, L. S. (2024) · IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) · doi:10.1109/saci60582.2024.10619902 · Cited by 2 · see citing works
CeHRes Roadmap to Improve Dementia Care
van Gemert‐Pijnen, J. E. W. C., & Span, M. (2015) · Springer eBooks · doi:10.1007/978-3-319-01904-8_15-1 · Cited by 2 · see citing works
Koskinen, J. S. S., & Rantanen, M. M. (2020) · Communications in computer and information science · doi:10.1007/978-3-030-57847-3_2 · Cited by 1 · see citing works
van Schalkwyk, A., Grobbelaar, P. S., Herselman, M. E., & Vermeulen, E. (2022) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice/itmc-iamot55089.2022.10033267 · Cited by 1 · see citing works
Patient Portal Use in Diabetes Management: Literature Review (Preprint)Preprint
Sun, R., Korytkowski, M. T., Sereika, S. M., Saul, M. I., Li, D., & Burke, L. E. (2018) · doi:10.2196/preprints.11199 · Cited by 1 · see citing works
- Authors
- Sieverink, F., Kelders, S. M., Braakman-Jansen, L. M. A., & van Gemert-Pijnen, J. E. W. C.
- Affiliations
- University of Twente (NL)
- Department of Psychology, Health and Technology, Center for eHealth Research and Disease Management, University of Twente, Enschede, Netherlands
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2014-03
- Volume
- 8
- Issue
- 2
- Pages
- 247-255
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC4455425
- OpenAlex
- W2170307054
- Cited by
- 30
- References
- 20
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 3 · 2019: 4 · 2018: 7 · 2017: 4 · 2016: 3 · 2015: 2 · 2014: 1
- FWCI
- 6.09
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of Twente Research Information (publishedVersion)
- University of Twente Research Information (submittedVersion, other-oa)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Keywords
- personal health records, type 2 diabetes, log analysis, user navigation behavior, patient adherence, chronic disease management, system design improvement, patient education
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