Patient-Generated Health Data (PGHD) Interoperability: An Integrative Perspective
Open accessAbstract
With advances in Digital Health (DH) tools, it has become much easier to collect, use, and share patient-generated health data (PGHD). This wealth of data could be efficiently used in monitoring and controlling chronic illnesses as well as predicting health outcome. Although integrating PGHD into clinical practice is currently in a promising stage, there are several technical challenges and usage barriers that hinder the full utilization of the PGHD potential in clinical care and research. This paper aims to address PGHD opportunities and challenges while developing the DH-Convener project to integrate PGHD into the Electronic Health Record in Austria (ELGA). Accordingly, it provides an integrative technical-clinical-user approach for developing a fully functional health ecosystem for exchanging integrated data among patients, healthcare providers, and researchers.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Healthcare interoperability allows health institutions to build the technology infrastructure needed to maximize the value of their EHR data and provide more comprehensive care.
“Approximately, healthcare interoperability allows health institutions to build the technology infrastructure needed to maximize the value of their EHR data and provide more comprehensive care [21].”
From Interoperability of heterogeneous health information systems: a systematic literature review (2023) · cites this paper as [21]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Why digital medicine depends on interoperability
Lehne, M., Sass, J., Essenwanger, A., Schepers, J., & Thun, S. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0158-1 · Cited by 501 · see citing works
Patient generated health data use in clinical practice: A systematic review
Demiris, G., Iribarren, S., Sward, K. A., Lee, S., & Yang, R. (2019) · Nursing Outlook · doi:10.1016/j.outlook.2019.04.005 · Cited by 116 · see citing works
Personalized medicine: risk prediction, targeted therapies and mobile health technology
Hayes, D. F., Markus, H. S., Leslie, R. D., & Topol, E. J. (2014) · BMC Medicine · doi:10.1186/1741-7015-12-37 · Cited by 105 · see citing works
Present and Future Trends in Consumer Health Informatics and Patient-Generated Health Data
Lai, A. M., Hsueh, P.-Y. S., Choi, Y. K., & Austin, R. R. (2017) · Yearbook of Medical Informatics · doi:10.15265/iy-2017-016 · Cited by 84 · see citing works
Lavallee, D. C., Lee, J. R., Austin, E. J., Bloch, R., Lawrence, S. O., McCall, D., Munson, S. A., Nery-Hurwit, M. B., & Amtmann, D. (2020) · mHealth · doi:10.21037/mhealth.2019.09.17 · Cited by 83 · see citing works
Slevin, P., & Caulfield, B. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811810-8.00013-0 · Cited by 58 · see citing works
Tiase, V. L., Hull, W., McFarland, M., Sward, K. A., Fiol, G. D., Staes, C. J., Weir, C. R., & Cummins, M. R. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-033073 · Cited by 25 · see citing works
Karampela, M., Ouhbi, S., & Isomursu, M. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856550 · Cited by 15 · see citing works
Gutenberg, J., Kulnik, S. T., Hussein, R., Stütz, T., Niebauer, J., & Crutzen, R. (2020) · Studies in health technology and informatics · doi:10.3233/shti200730 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Interoperability of heterogeneous health information systems: a systematic literature review
Torab-Miandoab, A., Samad-Soltani, T., Jodati, A., & Rezaei-Hachesu, P. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02115-5 · Cited by 393 · see citing works
- Authors
- Hussein, R., Crutzen, R., Gutenberg, J., Kulnik, S. T., Sareban, M., & Niebauer, J.
- Affiliations
- Ludwig Boltzmann Institute for Digital Health and Prevention (AT)
- Maastricht University (NL)
- Paracelsus Medical University (AT)
- Venue
- Studies in Health Technology and Informatics
- Publisher
- IOS Press
- Published
- 2021-05-27
- Volume
- 281
- Pages
- 228-232
- ISSN
- 0926-9630 (ISSN-L)
- 1879-8365
- OpenAlex
- W3164696196
- Cited by
- 24
- References
- 9
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 9 · 2022: 4 · 2021: 1
- FWCI
- 10.95
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Studies in health technology and informatics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by-nc)
- Research Publications (Maastricht University) (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 › Health Information Management › Innovation in Digital Healthcare Systems
- Keywords
- patient-generated health data, interoperability, digital health, electronic health records, Elga, data integration, chronic disease management, health information exchange, healthcare ecosystem
- MeSH terms
- Austria, Humans, Ecosystem, Electronic Health Records
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review