mHEART4U: Clinical Decision Support System for Remote Monitoring of Cardiovascular Disease Patients
Study Details
Study Description
Brief Summary
Cardiovascular diseases (CVD) are the leading cause of death worldwide, taking an estimated 17.9 million lives each year. The reduction of CVD-related mortality and morbidity is a key global health priority. Cardiac rehabilitation (CR) is a multi-factorial and comprehensive intervention in secondary prevention, being recommended in international guidelines. Core components in CR include patient assessment, physical activity counseling, nutritional counseling, risk factor control, patient education, and psychosocial management. CR has been shown to reduce mortality, hospital readmissions, costs, as well as to improve physical fitness, quality of life, and psychological well-being. However, despite the recommendations and proven benefits, acceptance and adherence remain low. Access to health technologies in all primary and secondary healthcare facilities can be essential to ensure that those in need receive treatment and counseling.
Using mobile health (mHealth) solutions may contribute to more personalized and tailored patient recommendations according to their specific needs. Also, these technologies contribute to increasing the flexibility, quality, and efficiency of the services provided by health institutions.
Time constraints, patient overpopulation, and complex guidelines require alternative solutions for real-time patient monitoring. Rapidly evolving e-health technology combined with clinical decision support systems (CDSS) provides an effective solution to these problems. There are several computerized CDSS for managing chronic diseases; however, to the best of our knowledge, there are none for the e-management of patients with CVD.
The purpose of this transdisciplinary research project is to develop and evaluate a user-friendly, comprehensive CDSS for remote monitoring of CVD patients. The CDSS will suggest a monitoring plan for the patient, advise the mHealth tools (apps and wearables) adapted to patient needs, and collect data. The primary outcome will be the reduction of recurrent cardiovascular events (a composite of cardiovascular rehospitalization or urgent consultation, unplanned revascularization, cardiovascular mortality, or worsening heart failure).
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: mHeart.4u The mHEART.4U intervention includes the use of an online Clinical Decision Support System (CDSS) for remote patient monitoring. According to the patient needs and profile, the CDSS will suggest a monitoring plan for the patient. The mHEART.4U kit will include mobile apps and wearables, such as heart rate, blood pressure, peripheral oxygen saturation (SpO2), sleep and step trackers, symptoms, lifestyle self-monitoring tools, medication reminders or motivational resources. The intervention length will be 6 months and will take into account the most recent guidelines on Cardiac Rehabilitation. |
Combination Product: mHeart.4u
The mHeart.4U is a multiple-components intervention entailing the adoption and use of technological devices and self-management recommendations tailored to behavioural modifications (e.g. physical exercise and dietary patterns)
|
| No Intervention: Standard care This arm will receive treatment and care according to the prevailing practice at each of the cardiac hospital units. |
Outcome Measures
Primary Outcome Measures
- Recurrent cardiovascular event rates [Two measurement timepoints: 3-month (T1) and the 6-month (T2)]
This outcome is a composite of cardiovascular rehospitalization or urgent visit, unplanned revascularization, cardiovascular mortality, or worsening heart failure
Secondary Outcome Measures
- Quality of life score (assessed by the MacNew Heart Disease Health-related Quality of Life questionnaire) [Two measurement timepoints: 3-month (T1) and the 6-month (T2)]
The MacNew Heart Disease Health-related Quality of Life questionnaire consists of 27 items which fall into three domains (physical limitations domain scale, emotional function domain scale, and social function domain scale). Scoring of the MacNew is straight-forward. The maximum possible score in any domain is 7 (high quality of life) and the minimum is 1 (poor quality of life).
- Adherence to treatment score (assessed by the Therapeutic Self-care Scale) [Two measurement timepoints: 3-month (T1) and the 6-month (T2)]
The Therapeutic Self-care Scale total score (from 0 to 60 points) corresponds to a high level of performance in therapeutic self-care. The scale is designed to assess patients' ability to engage in four aspects of self-care: taking medications as prescribed by the doctor; identifying and managing symptoms; performing activities of daily living; and managing changes in condition.
- Body Mass Index (in Kg/m^2) [Two measurement timepoints: 3-month (T1) and the 6-month (T2)]
The Body Mass Index is a measure of body fat based on height and weight. It is calculated by a person's weight in kilograms divided by the square of height in meters.
- Health-Promoting Lifestyle score (assessed by the Health-Promoting Lifestyle Profile-II) [Two measurement timepoints: 3-month (T1) and the 6-month (T2)]
The Health-Promoting Lifestyle Profile-II consists of 52 health-promoting behavior items that are categorized into six subscales: health responsibility, spiritual growth, physical activity, interpersonal relationships, nutrition, and stress management. Each behavior is measured from 1 (never) to 4 (regularly). The total score of the scale ranges from 52 to 208 (higher scores represents healthier lifestyles).
Other Outcome Measures
- Cardiovascular risk assessed by the Systematic COronary Risk Evaluation (SCORE) [Baseline]
The Systematic COronary Risk Evaluation (SCORE) is derived from a large dataset of prospective European studies and predicts fatal atherosclerotic cardiovascular events over a ten year period. This relative risk estimation (percentage) is based on the following risk factors: gender, age, smoking, systolic blood pressure and total cholesterol.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Patients attending the cardiology outpatient clinics after the onset of acute cardiac event OR
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Patients attending the cardiology outpatient clinics who are engaged in a structured Cardiac Rehabilitation program
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Be able to communicate with the researcher
Exclusion Criteria:
- Participants will be excluded if they have New York Heart Association class III/IV heart failure, terminal disease, or significant non-cardio vascular disease exercise limitations.
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Escola Superior de Enfermagem de Coimbra
- Instituto Politécnico de Leiria
Investigators
- Principal Investigator: Pedro Sousa, PhD, Nursing School of Coimbra
Study Documents (Full-Text)
None provided.More Information
Publications
- Abreu A, Mendes M, Dores H, Silveira C, Fontes P, Teixeira M, Santa Clara H, Morais J. Mandatory criteria for cardiac rehabilitation programs: 2018 guidelines from the Portuguese Society of Cardiology. Rev Port Cardiol (Engl Ed). 2018 May;37(5):363-373. doi: 10.1016/j.repc.2018.02.006. Epub 2018 Apr 30. English, Portuguese.
- Authors/Task Force Members, Rydén L, Grant PJ, Anker SD, Berne C, Cosentino F, Danchin N, Deaton C, Escaned J, Hammes HP, Huikuri H, Marre M, Marx N, Mellbin L, Ostergren J, Patrono C, Seferovic P, Uva MS, Taskinen MR, Tendera M, Tuomilehto J, Valensi P, Zamorano JL; ESC Committee for Practice Guidelines (CPG), Zamorano JL, Achenbach S, Baumgartner H, Bax JJ, Bueno H, Dean V, Deaton C, Erol C, Fagard R, Ferrari R, Hasdai D, Hoes AW, Kirchhof P, Knuuti J, Kolh P, Lancellotti P, Linhart A, Nihoyannopoulos P, Piepoli MF, Ponikowski P, Sirnes PA, Tamargo JL, Tendera M, Torbicki A, Wijns W, Windecker S; Document Reviewers, De Backer G, Sirnes PA, Ezquerra EA, Avogaro A, Badimon L, Baranova E, Baumgartner H, Betteridge J, Ceriello A, Fagard R, Funck-Brentano C, Gulba DC, Hasdai D, Hoes AW, Kjekshus JK, Knuuti J, Kolh P, Lev E, Mueller C, Neyses L, Nilsson PM, Perk J, Ponikowski P, Reiner Z, Sattar N, Schächinger V, Scheen A, Schirmer H, Strömberg A, Sudzhaeva S, Tamargo JL, Viigimaa M, Vlachopoulos C, Xuereb RG. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: the Task Force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD). Eur Heart J. 2013 Oct;34(39):3035-87. doi: 10.1093/eurheartj/eht108. Epub 2013 Aug 30. Erratum in: Eur Heart J. 2014 Jul 14;35(27):1824.
- Leal A, Paiva C, Höfer S, Amado J, Gomes L, Oldridge N. Evaluative and discriminative properties of the Portuguese MacNew Heart Disease Health-related Quality of Life Questionnaire. Qual Life Res. 2005 Dec;14(10):2335-41.
- Quaosar GMAA, Hoque MR, Bao Y. Investigating Factors Affecting Elderly's Intention to Use m-Health Services: An Empirical Study. Telemed J E Health. 2018 Apr;24(4):309-314. doi: 10.1089/tmj.2017.0111. Epub 2017 Oct 4.
- Rawstorn JC, Ball K, Oldenburg B, Chow CK, McNaughton SA, Lamb KE, Gao L, Moodie M, Amerena J, Nadurata V, Neil C, Cameron S, Maddison R. Smartphone Cardiac Rehabilitation, Assisted Self-Management Versus Usual Care: Protocol for a Multicenter Randomized Controlled Trial to Compare Effects and Costs Among People With Coronary Heart Disease. JMIR Res Protoc. 2020 Jan 27;9(1):e15022. doi: 10.2196/15022.
- Rawstorn JC, Gant N, Direito A, Beckmann C, Maddison R. Telehealth exercise-based cardiac rehabilitation: a systematic review and meta-analysis. Heart. 2016 Aug 1;102(15):1183-92. doi: 10.1136/heartjnl-2015-308966. Epub 2016 Mar 2. Review.
- Santos P. The Role of Cardiovascular Risk Assessment in Preventive Medicine: A Perspective from Portugal Primary Health-Care Cardiovascular Risk Assessment. J Environ Public Health. 2020 Jan 30;2020:1639634. doi: 10.1155/2020/1639634. eCollection 2020. Review.
- Slater H, Campbell JM, Stinson JN, Burley MM, Briggs AM. End User and Implementer Experiences of mHealth Technologies for Noncommunicable Chronic Disease Management in Young Adults: Systematic Review. J Med Internet Res. 2017 Dec 12;19(12):e406. doi: 10.2196/jmir.8888. Review.
- Sousa P, Gaspar P, Vaz DC, Gonzaga S, Dixe MA. Measuring health-promoting behaviors: cross-cultural validation of the Health-Promoting Lifestyle Profile-II. Int J Nurs Knowl. 2015 Apr;26(2):54-61. doi: 10.1111/2047-3095.12065. Epub 2014 Nov 11.
- Su JJ, Yu DSF, Paguio JT. Effect of eHealth cardiac rehabilitation on health outcomes of coronary heart disease patients: A systematic review and meta-analysis. J Adv Nurs. 2020 Mar;76(3):754-772. doi: 10.1111/jan.14272. Epub 2020 Feb 3.
- mHEART.4U