Literature DB >> 31598792

The Potential of mHealth Applications in Improving Resistant Hypertension Self-Assessment, Treatment and Control.

Karla Santo1,2,3, Julie Redfern4,5.   

Abstract

PURPOSE OF REVIEW: To review the evidence supporting the use of mobile health (mHealth) apps to improve resistant hypertension self-assessment, treatment and control. RECENT
FINDINGS: mHealth apps have been used to directly measure blood pressure (BP) levels, either using the oscillometric method with automated inflatable cuffs or using pulse wave signals detected by smartphone technology without the need for cuffs. These app-based BP monitors tend to over or underestimate BP levels when compared to a gold standard aneroid sphygmomanometer. However, the differences in BP measurements are within the acceptable range of 5 mmHg pre-defined by the European Society of Hypertension International Protocol Revision 2010. mHealth apps are also used as tools to support physicians in improving hypertension treatment. App-based clinical decision support systems are innovative solutions, in which patient information is entered in the app and management algorithms provide recommendations for hypertension treatment. The use of these apps has been shown to be feasible and easily integrated into the workflow of healthcare professionals, and, therefore particularly useful in resource-limited settings. In addition, apps can be used to improve hypertension control by facilitating regular BP monitoring, communication between patients and health professionals, and patient education; as well as by reinforcing behaviours through reminders, including medication-taking and appointment reminders. Several studies provided evidence supporting the use of apps for hypertension control. Although some of the results are promising, there is still limited evidence on the benefits of using such mHealth tools, as these studies are relatively small and with a short-term duration. Recent research has shown that mHealth apps can be beneficial in terms of improving hypertension self-assessment, treatment and control, being especially useful to help differentiate and manage true and pseudo-resistant hypertension. However, future research, including large-scale randomised clinical trials with user-centred design, is crucial to further evaluate the potential scalability and effectiveness of such mHealth apps in the resistant hypertension context.

Entities:  

Keywords:  Applications; Apps; Control; Digital health; Hypertension; Mobile technology; Self-assessment; Treatment; mHealth

Mesh:

Year:  2019        PMID: 31598792     DOI: 10.1007/s11906-019-0986-z

Source DB:  PubMed          Journal:  Curr Hypertens Rep        ISSN: 1522-6417            Impact factor:   5.369


  37 in total

1.  A content analysis of smartphone-based applications for hypertension management.

Authors:  Nilay Kumar; Monica Khunger; Arjun Gupta; Neetika Garg
Journal:  J Am Soc Hypertens       Date:  2014-12-11

Review 2.  Adherence in Hypertension.

Authors:  Michel Burnier; Brent M Egan
Journal:  Circ Res       Date:  2019-03-29       Impact factor: 17.367

3.  BPcontrol. A Mobile App to Monitor Hypertensive Patients.

Authors:  Adrian Carrera; Marc Pifarré; Jordi Vilaplana; Josep Cuadrado; Sara Solsona; Jordi Mateo; Francesc Solsona
Journal:  Appl Clin Inform       Date:  2016-12-07       Impact factor: 2.342

4.  Comparing the effects of education using telephone follow-up and smartphone-based social networking follow-up on self-management behaviors among patients with hypertension.

Authors:  Tahereh Najafi Ghezeljeh; Sanaz Sharifian; Mehdi Nasr Isfahani; Hamid Haghani
Journal:  Contemp Nurse       Date:  2018-03-05       Impact factor: 1.787

5.  An ICT and mobile health integrated approach to optimize patients' education on hypertension and its management by physicians: The Patients Optimal Strategy of Treatment(POST) pilot study.

Authors:  Fabio Albini; Camilla Torlasco; Davide Soranna; Andrea Faini; Renata Ciminaghi; Ada Celsi; Matteo Benedetti; Antonella Zambon; Marco di Rienzo; Gianfranco Parati
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

6.  Resistant Hypertension: Detection, Evaluation, and Management: A Scientific Statement From the American Heart Association.

Authors:  Robert M Carey; David A Calhoun; George L Bakris; Robert D Brook; Stacie L Daugherty; Cheryl R Dennison-Himmelfarb; Brent M Egan; John M Flack; Samuel S Gidding; Eric Judd; Daniel T Lackland; Cheryl L Laffer; Christopher Newton-Cheh; Steven M Smith; Sandra J Taler; Stephen C Textor; Tanya N Turan; William B White
Journal:  Hypertension       Date:  2018-11       Impact factor: 10.190

7.  Association of a Smartphone Application With Medication Adherence and Blood Pressure Control: The MedISAFE-BP Randomized Clinical Trial.

Authors:  Kyle Morawski; Roya Ghazinouri; Alexis Krumme; Julie C Lauffenburger; Zhigang Lu; Erin Durfee; Leslie Oley; Jessica Lee; Namita Mohta; Nancy Haff; Jessie L Juusola; Niteesh K Choudhry
Journal:  JAMA Intern Med       Date:  2018-06-01       Impact factor: 21.873

8.  Patients' views and experiences of technology based self-management tools for the treatment of hypertension in the community: A qualitative study.

Authors:  Liam Glynn; Monica Casey; Jane Walsh; Patrick S Hayes; Richard P Harte; David Heaney
Journal:  BMC Fam Pract       Date:  2015-09-09       Impact factor: 2.497

Review 9.  Smartphone Apps to Support Self-Management of Hypertension: Review and Content Analysis.

Authors:  Tourkiah Alessa; Mark S Hawley; Emma S Hock; Luc de Witte
Journal:  JMIR Mhealth Uhealth       Date:  2019-05-28       Impact factor: 4.773

10.  A new automatic blood pressure kit auscultates for accurate reading with a smartphone: A diagnostic accuracy study.

Authors:  Hongjun Wu; Bingjian Wang; Xinpu Zhu; Guang Chu; Zhi Zhang
Journal:  Medicine (Baltimore)       Date:  2016-08       Impact factor: 1.889

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  9 in total

Review 1.  [Artificial intelligence in cardiology : Relevance, current applications, and future developments].

Authors:  Bettina Zippel-Schultz; Carsten Schultz; Dirk Müller-Wieland; Andrew B Remppis; Martin Stockburger; Christian Perings; Thomas M Helms
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2021-01-15

2.  Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine.

Authors:  Anne Kuwabara; Sharlene Su; Jeffrey Krauss
Journal:  Am J Lifestyle Med       Date:  2019-12-13

Review 3.  Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis.

Authors:  Ghada Alhussein; Leontios Hadjileontiadis
Journal:  JMIR Mhealth Uhealth       Date:  2022-04-21       Impact factor: 4.947

4.  Intelligent Rehabilitation Assistance Tools for Distal Radius Fracture: A Systematic Review Based on Literatures and Mobile Application Stores.

Authors:  Yalan Chen; Yijun Yu; Xin Lin; Zhenwei Han; Zhe Feng; Xinyi Hua; Dongliang Chen; Xiaotao Xu; Yuanpeng Zhang; Guheng Wang
Journal:  Comput Math Methods Med       Date:  2020-09-29       Impact factor: 2.238

Review 5.  Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review.

Authors:  Ernest Osei; Tivani P Mashamba-Thompson
Journal:  Heliyon       Date:  2021-03-31

6.  Comparing the Acceptance of Mobile Hypertension Apps for Disease Management Among Patients Versus Clinical Use Among Physicians: Cross-sectional Survey.

Authors:  Bernhard Breil; Christel Salewski; Jennifer Apolinário-Hagen
Journal:  JMIR Cardio       Date:  2022-01-06

7.  Risk Prediction Model for Uncontrolled Hypertension in Chinese Community.

Authors:  Zhiping Gao; Shiqun Chen; Xiaoyu Huang; Jianfeng Ye; Jin Liu; Zhidong Huang; Jiyan Chen; Liwen Li; Yong Liu; Shuguang Lin
Journal:  Front Cardiovasc Med       Date:  2022-01-24

8.  mHealth Applications to Monitor Lifestyle Behaviors and Circadian Rhythm in Clinical Settings: Current Perspective and Future Directions.

Authors:  Iolanda Rosa; Marlene Lages; Carlos Grilo; Renata Barros; Maria P Guarino
Journal:  Front Public Health       Date:  2022-07-18

9.  A Comprehensive 6A Framework for Improving Patient Self-Management of Hypertension Using mHealth Services: Qualitative Thematic Analysis.

Authors:  Ting Song; Fang Liu; Ning Deng; Siyu Qian; Tingru Cui; Yingping Guan; Leonard Arnolda; Zhenyu Zhang; Ping Yu
Journal:  J Med Internet Res       Date:  2021-06-21       Impact factor: 5.428

  9 in total

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