Interdisciplinary Mobile Health Model to Improve Clinical Care After Heart Transplantation: Implementation Strategy Study

Tacrolimus and Cyclosporin Pharmacotherapy, Detection Methods, Cytochrome P450 Enzymes after Heart Transplantation

BACKGROUND

Advances in organ transplantation were made after the discovery of the pure form of cyclosporine by Dr Jean Borel in the 1970s. In fact, in clinical practice achieving a delicate balance in circulating immunosuppressive necessitate focus on the difficult task of posttransplant therapeutic drug monitoring.

OBJECTIVE

The purpose of this study was to determine the pharmacologic properties of cyclosporine- tacrolimus, detection methods, and the effects on the activity of cytochrome P450 enzymes when prescribing the most efficient treatments in forms of polypharmacy for the recipients of heart transplantation.

METHODS

Scientific literature on the interactions of tacrolimus and cyclosporine with human cytochrome P450 enzymes was searched using PUBMED.Gov (https://pubmed.ncbi.nlm.nih.gov/), Web of Science, and Scopus.

RESULTS

Prescription immunosuppressive drugs based on polypharmacy accompanied by induction agents could result in hidden neurotoxicity and nephrotoxicity. A literature search shows that cyclosporine prescription with antihypertensives drugs needs close monitoring. Co-administration of tacrolimus and diltiazem or verapamil needs a decrease in the tacrolimus dose by 20-50%. Vigilant attention to the lowest possible statin dose is needed when coadministered with fluvastatin or pravastatin. Polypharmacy based on ticlopidine, clopidogrel, and cyclosporine or tacrolimus needs monitoring of immunosuppressive drug levels for several months. A prescription with clotrimazole or fluconazole needs close monitoring, and itraconazole or ketoconazole needs to reduce the initial dose by 50%. Combination with nefazodone needs to be avoided, and alternative drugs such as sertraline or citalopram could be prescribed in addition to further monitoring consideration. In prescription with phenytoin, the bound and free phenytoin levels need close monitoring.

CONCLUSION

Polypharmacy based on tacrolimus or cyclosporine needs vigilant therapeutic drug monitoring due to the cytochrome P450 enzymes associated with biochemical variables in metabolic pathways. Further attention to polypharmacy should be given to circulate drugs that could hide pharmacokinetics interactions associated with infections, malignancies, chronic kidney disease, and rejection after organ transplantation.

Systematic review on the involvement and engagement of patients as advisers for the organisation of organ transplantation services

OBJECTIVES

This systematic review aims to derive practical lessons from publications on patient involvement and engagement in the organisation of organ transplantation services.

DESIGN

This systematic review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses. Inclusion criteria for the analysis of publications in English cited in the databases PubMed and Web of Science until 6 December 2022 required that patients participated as advisers in the organisation of organ transplantation services. Quality assessment was performed using the Guidance for Reporting Involvement of Patients and the Public (GRIPP) 2 small form and the Critical Appraisal Skills Programme (CASP) tool for the assessment of the risks of bias.

RESULTS

Deployed search strings identified 2263 records resulting in a total of 11 articles. The aims and strategies, deployed methods, observed effects, observed barriers and proposed improvements for the future varied vastly. All reported that well-developed programmes involving and engaging patients at an organisational level provide additional benefits for patients and foster patient-centred care. Lessons learnt include: (1) to empower patients, the information provided to them should be individualised to prioritise their needs; (2) financial as well as organisational resources are important to successfully implement patient involvement and engagement; (3) systematic feedback from patients in organisational structures to health providers is required to improve clinical workflows and (4) the consideration of ethical issues and the relationship between investigators and participating patients should be clarified and reported.

CONCLUSIONS

Actionable management recommendations could be derived. The quantitative impact on clinical outcome and economic clinical process improvements remains to be investigated. Study quality can be improved using the GRIPP 2 guidance and the CASP tool.

PROSPERO REGISTRATION NUMBER

CRD42022186467.

Feasibility of a new model of care for allogeneic stem cell transplantation recipients facilitated by eHealth: The MY-Medula pilot study

BACKGROUND

The use of allogeneic stem cell transplantation (allo-SCT) for the treatment of hematologic diseases is steadily increasing. However, allo-SCT has the downside of causing considerable treatment-related morbidity and mortality. Mobile technology applied to healthcare (mHealth) has proven to be a cost-effective strategy to improve care and offer new services to people with multimorbidity, but there are few data on its usefulness in allo-SCT recipients.

OBJECTIVE

The aim of this report was to describe a new integrated healthcare model facilitated by an mHealth platform, named EMMASalud-MY-Medula, and to report the results of a le.

STUDY DESIGN

The MY-Medula platform development approach consisted of 4 phases. Firstly, patient and healthcare professional needs were identified and technological development and pre-testing tests were conducted (phases 1-3, January 2016-March 2021). Then, a non-randomized, prospective, observational, single-center pilot study was conducted (October 2021-January 2022) at the adult Stem Cell Transplant Unit of a tertiary university hospital.

RESULTS

Twenty-eight volunteer allo-SCT recipients were included in the pilot study. Fifty percent were outpatients in the first-year post-SCT and the remaining 50% were affected by steroid-dependent graft-versus-host disease (SR-GVHD). All patients used MY-Medula application during the two-month follow-up period with a median number of visits to the application of 143 (range 6-477). A total of 2067 self-monitoring records were made, and 205 text messages were received, most of them related to symptoms description (47%) and doubts about medication (21%). In 3.4% of the cases drug dose adjustments were performed by the pharmacist because of dosing errors or interactions. At the end of the study, a 6-question Likert-type questionnaire for patients and a 22-question test for healthcare professionals showed a high degree of satisfaction (95% and 100% respectively) with the new healthcare pathway.

CONCLUSIONS

Re-engineering allo-SCT recipients follow-up into an integrated, multidisciplinary model of care facilitated by mHealth tools is feasible and has been associated with a high usability and degree of satisfaction by patients and healthcare professionals. A randomized trial aiming to determine the cost-effectiveness of MY-Medula-based follow-up post-SCT is currently enrolling participants.

Does an eHealth Intervention Reduce Complications and Healthcare Resources? A mHeart Single-Center Randomized-Controlled Trial

(1) Background: In the mHeart trial, we showed that an eHealth intervention, mHeart, improved heart transplant (HTx) recipients' adherence to immunosuppressive therapy compared with the standard of care. Herein, we present the analysis assessing whether mHeart reduces complication frequency and healthcare resource use, and whether this reduction depends on patients' adherence. (2) Methods: The mHeart was a single-center randomized-controlled trial (IIBSP-MHE-2014-55) in 134 adult HTx recipients (n = 71 intervention; n = 63 controls). The endpoints were mortality, complications, and resource use during follow-up (mean 1.6 ± 0.6 years). (3) Results: A significantly lower proportion of HTx recipients in mHeart had echocardiographic alteration (2.8% vs. 13.8%; p = 0.02), cardiovascular events (0.35% vs. 2.4%; p = 0.006), infections (17.2% vs. 56%; p = 0.03), and uncontrolled Hba1c (40.8% vs. 59.6%; p = 0.03) than controls. In addition, a significantly lower proportion of patients in the intervention needed hospital (32.4% vs. 56.9%; p = 0.004) or urgent admissions (16.9% vs. 41.4%; p = 0.002) and emergency room visits (50.7% vs. 69.0%; p = 0.03). Adherence status (measured by the self-reported SMAQ) influenced only controls regarding hospitalizations and emergency room visits. Differences were not significant on deaths (intervention 4.2% vs. control 9.5%; p = 0.4) (4) Conclusions: the mHeart strategy significantly reduced the occurrence of the studied post-transplant complications and the need for medical attention in HTx recipients. Adherence status influenced controls in their need for medical care.

Emerging Artificial Intelligence–Empowered mHealth: Scoping Review

Background

Artificial intelligence (AI) has revolutionized health care delivery in recent years. There is an increase in research for advanced AI techniques, such as deep learning, to build predictive models for the early detection of diseases. Such predictive models leverage mobile health (mHealth) data from wearable sensors and smartphones to discover novel ways for detecting and managing chronic diseases and mental health conditions.

Objective

Currently, little is known about the use of AI-powered mHealth (AIM) settings. Therefore, this scoping review aims to map current research on the emerging use of AIM for managing diseases and promoting health. Our objective is to synthesize research in AIM models that have increasingly been used for health care delivery in the last 2 years.

Methods

Using Arksey and O’Malley’s 5-point framework for conducting scoping reviews, we reviewed AIM literature from the past 2 years in the fields of biomedical technology, AI, and information systems. We searched 3 databases, PubsOnline at INFORMS, e-journal archive at MIS Quarterly, and Association for Computing Machinery (ACM) Digital Library using keywords such as “mobile healthcare,” “wearable medical sensors,” “smartphones”, and “AI.” We included AIM articles and excluded technical articles focused only on AI models. We also used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) technique for identifying articles that represent a comprehensive view of current research in the AIM domain.

Results

We screened 108 articles focusing on developing AIM models for ensuring better health care delivery, detecting diseases early, and diagnosing chronic health conditions, and 37 articles were eligible for inclusion, with 31 of the 37 articles being published last year (76%). Of the included articles, 9 studied AI models to detect serious mental health issues, such as depression and suicidal tendencies, and chronic health conditions, such as sleep apnea and diabetes. Several articles discussed the application of AIM models for remote patient monitoring and disease management. The considered primary health concerns belonged to 3 categories: mental health, physical health, and health promotion and wellness. Moreover, 14 of the 37 articles used AIM applications to research physical health, representing 38% of the total studies. Finally, 28 out of the 37 (76%) studies used proprietary data sets rather than public data sets. We found a lack of research in addressing chronic mental health issues and a lack of publicly available data sets for AIM research.

Conclusions

The application of AIM models for disease detection and management is a growing research domain. These models provide accurate predictions for enabling preventive care on a broader scale in the health care domain. Given the ever-increasing need for remote disease management during the pandemic, recent AI techniques, such as federated learning and explainable AI, can act as a catalyst for increasing the adoption of AIM and enabling secure data sharing across the health care industry.

Effectiveness of mobile health-based self-management application for posttransplant cares: A systematic review

BACKGROUND AND AIMS

Patients after transplantation need medical management for the rest of their lives, and self-management seems to lead to greater adherence to medical standards, improve early physical changes, and increase patient empowerment. The main objective of this article is to systematic review of the consideration to mobile health applications (m-Health apps) used in transplantation.

METHODS

A systematic search was conducted MEDLINE (through PubMed), Web of Science, Scopus, and Science Direct from inception to November 2020. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement was used in this study. Comprehensive research was carried out using a combination of keywords and MeSH terms associated with m-Health, empowerment, self-management, and transplantation. Two independent reviewers screened titles and abstracts, assessed full-text articles, and extracted data from articles that met inclusion criteria. Eligible studies were original research articles that included posttransplant care and mobile phone-based applications to support self-management and self-care. Also, thesis, book chapters, letters to editors, short briefs, reports, technical reports, book reviews, systematic reviews, or meta-analysis were excluded.

RESULTS

We divided all the reviewed articles into four categories, self-management (medication adherence, adherence to medical regimen, and remote monitoring), evaluation, interaction, and interface; 37.5% of the studies were focused on lung transplantation. In 56.25% of the studies, medication adherence was considered because one of the main reasons for the rejection and graft loss is stated medication nonadherence. Also, 62.5% of the studies demonstrated that the use of m-health improved medication adherence and self-management in transplantation.

CONCLUSIONS

The use of m-Health apps interventions to self-management after transplantation has shown promising feasibility and acceptability, and there is modest evidence to support the efficacy of these interventions. We found that m-Health solutions can help the patient in self-management in many ways after transplantation.

Mobile Health to Improve Adherence and Patient Experience in Heart Transplantation Recipients: The mHeart Trial

Non-adherence after heart transplantation (HTx) is a significant problem. The main objective of this study was to evaluate if a mHealth strategy is more effective than standard care in improving adherence and patients’ experience in heart transplant recipients. Methods: This was a single-center, randomized controlled trial (RCT) in adult recipients >1.5 years post-HTx. Participants were randomized to standard care (control group) or to the mHeart Strategy (intervention group). For patients randomized to the mHeart strategy, multifaceted theory-based interventions were provided during the study period to optimize therapy management using the mHeart mobile application. Patient experience regarding their medication regimens were evaluated in a face-to-face interview. Medication adherence was assessed by performing self-reported questionnaires. A composite adherence score that included the SMAQ questionnaire, the coefficient of variation of drug levels and missing visits was also reported. Results: A total of 134 HTx recipients were randomized (intervention N = 71; control N = 63). Mean follow-up was 1.6 (SD 0.6) years. Improvement in adherence from baseline was significantly higher in the intervention group versus the control group according to the SMAQ questionnaire (85% vs. 46%, OR = 6.7 (2.9; 15.8), p-value < 0.001) and the composite score (51% vs. 23%, OR = 0.3 (0.1; 0.6), p-value = 0.001). Patients’ experiences with their drug therapy including knowledge of their medication timing intakes (p-value = 0.019) and the drug indications or uses that they remembered (p-value = 0.003) significantly improved in the intervention versus the control group. Conclusions: In our study, the mHealth-based strategy significantly improved adherence and patient beliefs regarding their medication regimens among the HTx population. The mHeart mobile application was used as a feasible tool for providing long-term, tailor-made interventions to HTx recipients to improve the goals assessed.