Benefits and Challenges of Remote Patient Monitoring as Perceived by Health Care Practitioners: A Systematic Review
Open accessAbstract
BACKGROUND: Remote patient monitoring (RPM), or telemonitoring, offers ways for health care practitioners to gather real-time information on the physiological conditions of patients. As telemedicine, and thus telemonitoring, is becoming increasingly relevant in today's society, understanding the practitioners' opinions is crucial. This systematic review evaluates the perspectives and experiences of health care practitioners with telemonitoring technologies. METHODS: A database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the selection of articles measuring health care practitioners' perspectives and experiences with RPM technologies published between 2017 and 2021. Only articles written in English were included. No statistical analysis was performed and thus this is a qualitative review. RESULTS: A total of 1605 studies were identified after the initial search. After applying the inclusion and exclusion criteria of this review's authors, 13 articles were included in this review. In all, 2351 practitioners' perspectives and experience utilizing RPM technology in a variety of medical specialties were evaluated through close- and open-ended surveys. Recurring themes emerged for both the benefits and challenges. Common benefits included continuous monitoring of patients to provide prompt care, improvement of patient self-care, efficient communication, increased patient confidence, visualization of health trends, and greater patient education. Challenges comprised increased workload, higher patient anxiety, data inaccuracy, disorienting technology, financial issues, and privacy concerns. CONCLUSION: Health care practitioners generally believe that RPM is feasible for application. Additionally, there is a consensus that telemonitoring strategies will become increasingly relevant. However, there are still drawbacks to the technology that need to be considered.
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?
Studies on remote patient monitoring confirm the importance of HCP involvement with digital tools.
“Studies on remote patient monitoring confirm the importance of HCP involvement with digital tools [44–48].”
From Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial (2025) · cites this paper as [44]
Numerous studies have highlighted the benefits of remote patient monitoring between clinic visits in detecting health deterioration earlier and enabling prompt intervention, particularly for individuals with chronic conditions.
“Numerous studies have highlighted the benefits of remote patient monitoring between clinic visits in detecting health deterioration earlier and enabling prompt intervention, particularly for individuals with chronic conditions [44–50].”
From Caregiver experiences of an integrative patient-centered digital health application for pediatric type 1 diabetes care: Findings from a pilot clinical trial (2025) · cites this paper as [44]
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
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283 · see citing works
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions
Sterne, J. A., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., et al. (2016) · BMJ · doi:10.1136/bmj.i4919 · Cited by 20,329 · see citing works
Wearable Sensors for Remote Health Monitoring
Majumder, S., Mondal, T., & Deen, M. (2017) · Sensors · doi:10.3390/s17010130 · Cited by 1,375 · see citing works
A Middle-Range Theory of Self-Care of Chronic Illness
Riegel, B. J., Jaarsma, T., & Strömberg, A. (2012) · Advances in Nursing Science · doi:10.1097/ans.0b013e318261b1ba · Cited by 1,088 · see citing works
Twenty years of telemedicine in chronic disease management – an evidence synthesis
Wootton, R. (2012) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2012.120219 · Cited by 545 · see citing works
Turakhia, M. P., Desai, M., Hedlin, H., Rajmane, A., Talati, N., Ferris, T., Desai, S., Nag, D., Patel, M., Kowey, P., et al. (2019) · American Heart Journal · doi:10.1016/j.ahj.2018.09.002 · Cited by 474 · see citing works
Smartwatch Algorithm for Automated Detection of Atrial Fibrillation
Bumgarner, J. M., Lambert, C. T., Hussein, A. A., Cantillon, D. J., Baranowski, B., Wolski, K., Lindsay, B. D., Wazni, O. M., & Tarakji, K. G. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.03.003 · Cited by 446 · see citing works
Walker, R. C., Tong, A., Howard, K., & Palmer, S. C. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.01.013 · Cited by 250 · see citing works
Information and communications technologies for elderly ubiquitous healthcare in a smart home
Deen, M. J. (2015) · Personal and Ubiquitous Computing · doi:10.1007/s00779-015-0856-x · Cited by 245 · see citing works
Patient-generated health data management and quality challenges in remote patient monitoring
Abdolkhani, R., Gray, K., Borda, A., & DeSouza, R. (2019) · JAMIA Open · doi:10.1093/jamiaopen/ooz036 · Cited by 127 · see citing works
Homko, C. J., Santamore, W. P., Whiteman, V. E., Bower, M., Berger, P. K., Geifman-Holtzman, O., & Bové, A. A. (2007) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2006.0034 · Cited by 120 · see citing works
Health Care After the COVID-19 Pandemic and the Influence of Telemedicine
Temesgen, Z., DeSimone, D. C., Mahmood, M., Libertin, C. R., Palraj, R., & Berbari, E. F. (2020) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2020.06.052 · Cited by 117 · see citing works
Randomised crossover trial of telemonitoring in chronic respiratory patients (TeleCRAFT trial)
Chatwin, M., Hawkins, G., Paniccia, L., Woods, A. P. M., Hanak, A., Lucas, R., Baker, E. H., Ramhamdany, E., Mann, B., Riley, J. P., et al. (2016) · Thorax · doi:10.1136/thoraxjnl-2015-207045 · Cited by 113 · see citing works
Gay, V. C., & Leijdekkers, P. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.5094 · Cited by 107 · see citing works
The effect of telemedicine on outcome and quality of life in pregnant women with diabetes
Dalfrà, M. G., Nicolucci, A., Lapolla, A., & on behalf of the, T. I. S. G. (2009) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2009.081213 · Cited by 105 · see citing works
Runkle, J., Sugg, M., Boase, D., Galvin, S. L., & C. Coulson, C. (2019) · DIGITAL HEALTH · doi:10.1177/2055207619828220 · Cited by 98 · see citing works
Marko, K. I., Krapf, J. M., Meltzer, A. C., Oh, J., Ganju, N., Martinez, A., Sheth, S., & Gaba, N. D. (2016) · JMIR Research Protocols · doi:10.2196/resprot.6167 · Cited by 97 · see citing works
Korpershoek, Y. J. G., Vervoort, S. C. J. M., Trappenburg, J. C. A., & Schuurmans, M. J. (2018) · BMC Health Services Research · doi:10.1186/s12913-018-3545-4 · Cited by 87 · cited 11× · see citing works
“35 Another major concern for the health care practitioners is the potential problem with patients relying heavily on RPM. 7,14,16 Patients may believe that their health care practitioners are continuously monitoring the data and may postpone contact.”
BackgroundResultInfluentialPérez‐Ferre, N., Galindo, M., Fernández, M. D., Velasco, V., de la Cruz, M. J., Martín, P., del Valle, L., & Calle‐Pascual, A. L. (2009) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2009.12.002 · Cited by 86 · see citing works
Engler, R. L., Routh, T. L., & Lucisano, J. Y. (2017) · Clinical Diabetes · doi:10.2337/cd17-0053 · Cited by 85 · see citing works
The STARPAHC collection: part of an archive of the history of telemedicine
Freiburger, G. A., Holcomb, M., & Piper, D. (2007) · Journal of Telemedicine and Telecare · doi:10.1258/135763307781458949 · Cited by 72 · see citing works
A qualitative study of COPD-patients’ experience of a telemedicine intervention
Nissen, L., & Lindhardt, T. (2017) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2017.08.004 · Cited by 68 · see citing works
Lanssens, D., Vonck, S., Storms, V., Thijs, I. M. V., Grieten, L., & Gyselaers, W. (2018) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/j.ejogrb.2018.02.015 · Cited by 66 · see citing works
Patients' Use of Self-Monitored Readings for Managing Everyday Life with COPD: A Qualitative Study
Huniche, L., Dinesen, B., Nielsen, C., Grann, O., & Toft, E. S. (2013) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2012.0135 · Cited by 50 · see citing works
Aamodt, I. T., Lycholip, E., Celutkiene, J., Strömberg, A., Atar, D., Falk, R. S., von Lueder, T., Hellesø, R., Jaarsma, T., & Lie, I. (2019) · Journal of Medical Internet Research · doi:10.2196/10362 · Cited by 49 · see citing works
The effectiveness of nurse‐led telemonitoring of asthma: results of a randomized controlled trial
Willems, D. C. M., Joore, M. A., Hendriks, J. J. E., Nieman, F. H. M., Severens, J. L., & Wouters, E. F. �. (2008) · Journal of Evaluation in Clinical Practice · doi:10.1111/j.1365-2753.2007.00936.x · Cited by 49 · see citing works
Ding, E., Svennberg, E., Wurster, C. J., Duncker, D., Manninger, M., Lubitz, S. A., Dickson, E. L., Fitzgibbons, T. P., AKOUM, N. W., Al‐Khatib, S. M., et al. (2020) · Cardiovascular Digital Health Journal · doi:10.1016/j.cvdhj.2020.06.002 · Cited by 41 · see citing works
Maguire, R., Connaghan, J., Arber, A., Klepacz, N., Blyth, K. G., McPhelim, J., Murray, P., Rupani, H., Chauhan, A., Williams, P., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/19180 · Cited by 38 · see citing works
Lundell, S., Modig, M., Holmner, Å., & Wadell, K. (2020) · JMIR mhealth and uhealth · doi:10.2196/16343 · Cited by 37 · see citing works
Jeffs, L. P., Jain, A. K., Man, R., Onabajo, N., Desveaux, L., Shaw, J., Hensel, J. M., Agarwal, P., Saragosa, M., Jamieson, T., et al. (2017) · BMC Nephrology · doi:10.1186/s12882-017-0557-y · Cited by 32 · see citing works
Thilly, N., Chanliau, J., Frimat, L., et al. (2017) · BMC Nephrology · doi:10.1186/s12882-017-0529-2 · Cited by 30 · see citing works
Hollenbach, J. P., Cushing, A. M., Melvin, E., McGowan, B., Cloutier, M. M., & Manice, M. (2016) · Journal of Asthma · doi:10.1080/02770903.2016.1263649 · Cited by 25 · see citing works
Lanssens, D., Vandenberk, T., Lodewijckx, J., Peeters, T., Storms, V., Thijs, I., Grieten, L., & Gyselaers, W. (2019) · Journal of Medical Internet Research · doi:10.2196/10887 · Cited by 25 · see citing works
Fraiche, A. M., Matlock, D. D., Gabriel, W., Rapley, F.-A., & Kramer, D. B. (2021) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2021.03.023 · Cited by 20 · see citing works
Sharif, F., Rahman, A., Tonner, E., Ahmed, H., Haq, I., Abbass, R., Asinger, S., & Sbai, M. (2020) · Perioperative Medicine · doi:10.1186/s13741-020-00166-0 · Cited by 19 · see citing works
Mergel, I. A. (2014) · JMIR mhealth and uhealth · doi:10.2196/mhealth.3694 · Cited by 15 · see citing works
Lakkireddy, D., Chung, M. K., Deering, T. F., Gopinathannair, R., Albert, C. M., Epstein, L. M., Harding, C. V., Hurwitz, J. L., Jeffery, C. C., Krahn, A. D., et al. (2020) · Heart Rhythm · doi:10.1016/j.hrthm.2020.06.012 · Cited by 15 · see citing works
Feasibility and Acceptability of Remotely Monitored Pedometer-Guided Physical Activity
Darvall, J. N., Parker, A. V., & Story, D. (2016) · Anaesthesia and Intensive Care · doi:10.1177/0310057x1604400415 · Cited by 13 · see citing works
Mansell, S. K., Kilbride, C., Wood, M. J., Gowing, F., & Mandal, S. (2020) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2019-000510 · Cited by 11 · see citing works
Craven, M. P., Andrews, J. A., Lang, A. R., Simblett, S. K., Bruce, S., Thorpe, S., Wykes, T., Morriss, R. K., & Hollis, C. P. (2020) · JMIR Formative Research · doi:10.2196/22756 · Cited by 10 · see citing works
Jeffs, L., Jamieson, T., Saragosa, M., Mukerji, G., Jain, A. K., Man, R., Desveaux, L., Shaw, J., Agarwal, P., Hensel, J. M., et al. (2018) · Patient Preference and Adherence · doi:10.2147/ppa.s181604 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Perspectives of Older Adults on Assistive Technology: Qualitative Study
Jaana, M., Lévesque Ryan, M., Tamim, H., Riachy, E., & Paré, G. (2025) · JMIR Human Factors · doi:10.2196/74214 · Cited by 6 · see citing works
Amed, S., Pinkney, S., Abdulhussein, F. S., Virani, A., Zachariuk, C., Tamana, S. K., Muralidharan, S., Görges, M., Barrett, B., van Rooij, T., et al. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000861 · Cited by 1 · see citing works
“Studies on remote patient monitoring confirm the importance of HCP involvement with digital tools [44–48].”
- Authors
- Serrano, L. P., Maita, K. C., Avila, F. R., Torres-Guzman, R. A., Garcia, J. P., Eldaly, A. S., Haider, C. R., Felton, C. L., Paulson, M. R., Maniaci, M. J., & Forte, A. J.
- Affiliations
- Mayo Clinic (US)
- Division of Plastic Surgery, Mayo Clinic, Jacksonville, FL, USA
- Corresponding author
- Forte, Antonio J
- ORCID
- Venue
- The Permanente Journal
- Publisher
- The Permanente Federation
- Published
- 2023-12-15
- Volume
- 27
- Issue
- 4
- Pages
- 100-111
- ISSN
- 1552-5767 (ISSN-L)
- 1552-5775
- PMC
- PMC10730976
- OpenAlex
- W4386944178
- Cited by
- 162
- References
- 41
- Citations by year
- 2026: 66 · 2025: 71 · 2024: 24 · 2023: 1
- FWCI
- 41.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- The Permanente Journal (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Social Sciences › Demography › Technology Use by Older Adults
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- remote patient monitoring, telemedicine, continuous patient monitoring, patient self-care, patient anxiety, data accuracy, privacy concerns, patient education
- MeSH terms
- Delivery of Health Care, Humans, Monitoring, Physiologic, Telemedicine
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