PatientConcept App: Key Characteristics, Implementation, and its Potential Benefit
Open accessAbstract
INTRODUCTION: In addition to a wide range of disease-related burdens, patients with multiple sclerosis (MS) are challenged by long-term medication and complex disease management plans, often leading to decreased adherence. Earlier studies have indicated that patient support through intensified communication can positively impact adherence. During recent years, the use of mobile health applications has gained importance in patient communication and disease management. OBJECTIVE: Our objective was to describe a novel software application providing innovative features that engage patient-physician contact and to evaluate users' acceptance. METHODS: A novel software application ensuring data security was developed. Various innovative modules have been implemented, enabling bidirectional communication between treating physicians and patients, supporting therapy monitoring and management, and allowing the collection of large sets of anonymous patient data. The currently conducted FASTER study will analyze the acceptance of patients and physicians using this novel application. RESULTS: PatientConcept is a free app available for download since 2016. Meanwhile, it has been successfully implemented. First preliminary results indicate high acceptance among users. The clinical benefit will have to be tested in larger patient populations. CONCLUSION: This ID-associated application may provide a secure, feasible, and cost-optimized possibility to intensify and simplify the communication between patients and their treating physicians, thus promising an exceptional benefit to both.
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Evaluation at the later stage was mostly focused on information available from app providers and app functionalities, such as assessing app quality, intervention relevance, or privacy risks.
“Evaluation at this stage was mostly focused on the information available from app providers and app functionalities, for instance, to assess app quality [74], intervention relevance [76], [77], or privacy risks speci cally [52].”
From Security and Privacy of mHealth Applications: A Scoping Review (2020) · cites this paper as [74]
The Results section, “App Development: Key Characteristics” (page not available), describes PatientConcept’s functions, and the Discussion considers their potential benefit as a health intervention. But the paper also reports patient and physician feedback in “Preliminary Results of the FASTER Study”; it does not establish that evaluation at a particular stage was mostly based on provider-supplied information and app functionality. (LLM, conf=0.78)
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Cites
Payne, H., Lister, C., West, J. H., & Bernhardt, J. M. (2015) · JMIR mhealth and uhealth · doi:10.2196/mhealth.3335 · Cited by 525 · see citing works
Devonshire, V. A., Lapierre, Y., Macdonell, R. A. L., Ramo-Tello, C. M., Patti, F., da Fontoura, P. P., Suchet, L., Hyde, R., Balla, I., Frohman, E. M., et al. (2010) · European Journal of Neurology · doi:10.1111/j.1468-1331.2010.03110.x · Cited by 339 · see citing works
Factors that influence adherence with disease-modifying therapy in MS
Treadaway, K., Cutter, G., Salter, A. R., LYNCH, S. G., Simsarian, J., Corboy, J. R., Jeffery, D., Cohen, B. A., Mankowski, K., Guarnaccia, J. B., et al. (2009) · Journal of Neurology · doi:10.1007/s00415-009-0096-y · Cited by 258 · see citing works
Patient Engagement and the Design of Digital Health
Birnbaum, F. A., Lewis, D. M., Rosen, R. K., & Ranney, M. L. (2015) · Academic Emergency Medicine · doi:10.1111/acem.12692 · Cited by 255 · see citing works
Impact of Adherence to Interferons in the Treatment of Multiple Sclerosis
Steinberg, S. C., Faris, R. J., Chang, C. F., Chan, A., & Tankersley, M. A. (2010) · Clinical Drug Investigation · doi:10.2165/11533330-000000000-00000 · Cited by 245 · see citing works
Does mHealth increase adherence to medication? Results of a systematic review
Anglada-Martinez, H., Riu-Viladoms, G., Martin-Conde, M., Rovira-Illamola, M., Sotoca-Momblona, J. M., & Codina-Jane, C. (2015) · International Journal of Clinical Practice · doi:10.1111/ijcp.12582 · Cited by 217 · see citing works
Menzin, J., Caon, C., Nichols, C. I., White, L. A., Friedman, M., & Pill, M. W. (2013) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2013.19.s1.s24 · Cited by 204 · see citing works
Haase, R., Schultheiß, T., Kempcke, R., Thomas, K., & Ziemssen, T. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2133 · Cited by 77 · see citing works
Facilitating Medication Adherence in Patients with Multiple Sclerosis
Remington, G. M., Rodriguez, Y., Logan, D., Williamson, C., & Treadaway, K. (2013) · International Journal of MS Care · doi:10.7224/1537-2073.2011-038 · Cited by 71 · see citing works
Fostering adherence to injectable disease-modifying therapies in multiple sclerosis
Lugaresi, A., Rottoli, M. R., & Patti, F. (2014) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2014.945523 · Cited by 59 · see citing works
Gerber, B., Cowling, T., Chen, G., Yeung, M., Duquette, P., & Haddad, P. (2017) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2017.10.001 · Cited by 35 · see citing works
Physical therapy provision in multiple sclerosis across Europe: a regional lottery?
Řasová, K., Martinková, P., Pavlikoma, M., Cattaneo, D., Jonsdottir, J., Henze, T., Baert, I., Asch, P. V., Santovo, C., Smedal, T., et al. (2015) · PubMed · Cited by 9 · see citing works
Gerber, B., Cowling, T., Chen, G., Rivest, D., Yeung, M., Duquette, P., Kindundu, C., Barbeau, M., & Haddad, P. (2016) · Value in Health · doi:10.1016/j.jval.2016.09.524 · Cited by 5 · see citing works
82. Kongress der Deutschen Gesellschaft für Neurologie
Mehrholz, J. (2010) · neuroreha · doi:10.1055/s-0030-1248946 · Cited by 1 · see citing works
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Security and Privacy of mHealth Applications: A Scoping Review
Nurgalieva, L., O'Callaghan, D., & Doherty, G. (2020) · IEEE Access · doi:10.1109/access.2020.2999934 · Cited by 132 · see citing works
“describe the practices they adopted for ensuring data security in the development of an app for multiple sclerosis patients [108].”
BackgroundSecurity and Privacy for mHealth and uHealth Systems: A Systematic Mapping Study
Iwaya, L. H., Ahmad, A., & Babar, M. A. (2020) · IEEE Access · doi:10.1109/access.2020.3015962 · Cited by 72 · see citing works
Gromisch, E. S., Turner, A. P., Haselkorn, J. K., Lo, A., & Agresta, T. P. (2020) · JAMIA Open · doi:10.1093/jamiaopen/ooaa067 · Cited by 44 · see citing works
Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice
Scholz, M., Haase, R., Schriefer, D., Voigt, I., & Ziemssen, T. (2021) · Brain Sciences · doi:10.3390/brainsci11020180 · Cited by 43 · see citing works
Karsten, M. M., Kühn, F., Pross, T., Blohmer, J., Hage, A. M., Fischer, F. H., Rose, M., Grittner, U., Gebert, P., Ferencz, J., et al. (2021) · Trials · doi:10.1186/s13063-021-05642-6 · Cited by 33 · see citing works
Thompson, C. M., Pulido, M. D., Babu, S., Zenzola, N., & Chiu, C. (2022) · Patient Education and Counseling · doi:10.1016/j.pec.2022.07.013 · Cited by 19 · see citing works
Mobile apps used for people living with multiple sclerosis: A scoping review
Howard, Z., Win, K. T., & Guan, V. X. (2023) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2023.104628 · Cited by 16 · see citing works
Privacy and security in digital therapeutics
Nurgalieva, L., & Doherty, G. J. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90045-4.00002-2 · Cited by 7 · see citing works
An ID-Associated Application to Facilitate Patient-Tailored Management of Multiple Sclerosis
Lang, M., Rau, D., Cepek, L., Cürten, F., Ringbauer, S., & Mayr, M. (2021) · Brain Sciences · doi:10.3390/brainsci11081061 · Cited by 5 · see citing works
Self-citationHage, A. M., Gebert, P., Kühn, F., Pross, T., Grittner, U., & Karsten, M. M. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19148284 · Cited by 2 · see citing works
Lang, M., Ringbauer, S., Mayr, M., & Cepek, L. (2019) · Clinical Research and Trials · doi:10.15761/crt.1000266 · Cited by 2 · see citing works
Self-citationKarsten, M. M., Kühn, F., Pross, T., Blohmer, J.-U., Hage, A. M., Fischer, F., Rose, M., Grittner, U., Gebert, P., Ferencz, J., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16696558
Karsten, M. M., Kühn, F., Pross, T., Blohmer, J.-U., Hage, A. M., Fischer, F., Rose, M., Grittner, U., Gebert, P., Ferencz, J., et al. (2021) · Figshare · doi:10.6084/m9.figshare.16696561
Nees, J., Kiermeier, S., Silchmüller, F. J., Keymling, M., Kratz, C. P., Maatouk, I., & Schott, S. (2026) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-026-08308-3
- Authors
- Lang, M., Mayr, M., Ringbauer, S., & Cepek, L.
- Corresponding author
- Lang, Michael
- Venue
- Neurology and Therapy
- Published
- 2019-03-26
- Volume
- 8
- Issue
- 1
- Pages
- 147-154
- ISSN
- 2193-6536 (ISSN-L)
- 2193-8253
- PMC
- PMC6534645
- OpenAlex
- W2923875567
- Cited by
- 14
- References
- 14
- Citations by year
- 2026: 1 · 2023: 1 · 2022: 3 · 2021: 5 · 2020: 3 · 2019: 1
- FWCI
- 4.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Neurology and Therapy (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Sanofi
- Sanofi Genzyme
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Keywords
- multiple sclerosis, mobile health apps, patient-physician communication, medication adherence, treatment monitoring, patient engagement, user acceptance, data security
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