Are patient characteristics and modes of delivery associated with completion of cardiac rehabilitation? A national registry analysis

Tang, Lars Hermann; Harrison, Alexander; Skou, Søren Thorgaard; Taylor, Rod S; Dalal, Hayes; Doherty, Patrick

doi:10.1016/j.ijcard.2022.05.007

Cited by 8 publications

(5 citation statements)

References 34 publications

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“…Offering personalized CR delivery methods and supporting patients towards the most likely suitable form of CR should become the standard care in hospitals. Rolling out these CR programs in a real world setting will allow for the gathering of real-world data, which not always corresponds with the results obtained in RCTs, as shown by Tang et al ( 26 ). In approximately half of European countries ≥1 CR programs offer alternative CR delivery methods, but this does not mean that each program in the country does so and it still leaves many countries who offer only centre-based CR ( 31 ).…”

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

“…The most intuitive approach would be to let patients choose their preferred delivery method of CR and several recent studies have investigated this approach ( 20 – 25 ), but each with substantial limitations and shortcomings. First, the content of the CR programs differed substantially, with marked differences in exercise interventions (frequency, intensity, time and type) between the different delivery modes or even comparisons between exercise interventions and educational programs, making a direct comparison invalid ( 24 , 26 ). Second, a cross-sectional observational study design was often used with the main outcomes being questionnaires aiming to investigate barriers and enablers to different CR delivery modes ( 21 , 23 ).…”

Section: Finding the Right Cr Program For The Right Patientmentioning

confidence: 99%

“…A second approach to find the best match between patient and program consists of incorporating the patient profile as a determinant in the decision process. A large retrospective study by Tang et al using the UK National Audit of Cardiac Rehabilitation (NACR) database, found that patients choosing home-based CR differed significantly from the populations in centre-based or hybrid CR and had lower completion rates of their CR program ( 26 ). Given that home-based programs were developed to increase uptake and adherence to CR in populations who are otherwise difficult to reach, these data suggest that the program did not reach the right patients.…”

Section: Finding the Right Cr Program For The Right Patientmentioning

confidence: 99%

See 2 more Smart Citations

The changing landscape of cardiac rehabilitation and the power of personalized therapy

Claes,

Kuznetsova,

Cauwenberghs

et al. 2024

Front. Cardiovasc. Med.

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Section: Discussion and Future Perspectivesmentioning

confidence: 99%

Section: Finding the Right Cr Program For The Right Patientmentioning

confidence: 99%

Section: Finding the Right Cr Program For The Right Patientmentioning

confidence: 99%

See 1 more Smart Citation

The changing landscape of cardiac rehabilitation and the power of personalized therapy

Claes,

Kuznetsova,

Cauwenberghs

et al. 2024

Front. Cardiovasc. Med.

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“…However, a national registry analysis of patients' characteristics and modes of delivery associated with the completion of cardiac rehabilitation found that home-based rehabilitation service delivery was associated with a reduced likelihood of rehabilitation completion. 46 While this may be the case, home-based services present clients with convenience and less disruption in their everyday lives. 47 Therefore, a combination of different modes considering the context and clients' needs would increase physical rehabilitation coverage and strengthen primary healthcare.…”

Section: Discussionmentioning

confidence: 99%

Evidence of community health workers’ delivery of physical rehabilitation services in sub-Saharan Africa: a scoping review

Mapulanga,

Kgarosi,

Maluleke

et al. 2024

BMJ Open

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ObjectivesTo map the evidence and scope of physical rehabilitation services delivered by community health workers (CHWs) in sub-Saharan Africa (SSA).DesignScoping reviewData sourcesPubMed, Scopus, Cochrane Central and databases within the EBSCOhost platform. We also searched other literature sources including reference lists, conference presentations and organisational websites such as WHO, Ministries of Health and non-governmental organisations in SSA.Eligibility criteria for selection of studiesArticles presenting evidence on CHWs’ delivery of physical rehabilitation services in SSA from September 1978 to June 2023.Data extraction and synthesisScreening was conducted by two reviewers and was guided by the inclusion criteria. Thematic content analysis of data was employed. The results are presented according to the Preferred Reporting Items for Systematic Review and Meta-Analysis extension for scoping reviews.ResultsA total of 6996 articles were identified through various databases, with only 20 studies qualifying for data extraction. Evidence was presented by Eritrea, Ethiopia, Malawi, Mauritius, Namibia, South Africa and Uganda. Assessments, case management, health education, community liaison with support, health systems linkage and administration were the CHWs’ scope of practice identified. The review identified home-based, community-based, community and facility-based, home and community-based and facility-based as modes of delivery. The barriers experienced are resources, societal and community attitudes, governance, geographical barriers and delivery capacity, while proximity to the community, positive job attitude and support with collaboration facilitated service delivery.ConclusionTraining and integrating CHWs in national health care systems, with careful selection of existing CHWs, would minimise the barriers faced.

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“…Second, being able to predict adherence to home-based CR could contribute to better allocation of resources. Tang [66] showed that patient characteristics influence the choice of a certain type of CR delivery mode. The clinician could use this information to advise for or against home-based CR for a specific patient, increasing the likelihood of a match between patient and CR program.…”

Section: Discussionmentioning

confidence: 99%

Predicting Adherence to Home-Based Cardiac Rehabilitation with Data-Driven Methods

et al. 2023

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Cardiac rehabilitation (CR) focuses on the improvement of health or the prevention of further disease progression after an event. Despite the documented benefits of CR programs, the participation remains suboptimal. Home-based CR programs have been proposed to improve uptake and adherence. The goal of this study was to apply an end-to-end methodology including machine learning techniques to predict the 6-month adherence of cardiovascular disease (CVD) patients to a home-based telemonitoring CR program, combining patients’ clinical information with their actual program participation during a short familiarization phase. Fifty CVD patients participated in such a program for 6 months, enabling personalized guidance during a phase III CR study. Clinical, fitness, and psychological data were measured at baseline, whereas actual adherence, in terms of weekly exercise session duration and patient heart rate, was measured using wearables. Hierarchical clustering was used to identify different groups based on (1) patients’ clinical baseline characteristics, (2) exercise adherence during the familiarization phase, and (3) the whole program adherence, whereas the output of the clustering was determined using repetitive decision trees (DTs) and random forest (RF) techniques to predict long-term adherence. Finally, for each cluster of patients, network analysis was applied to discover correlations of their characteristics that link to adherence. Based on baseline characteristics, patients were clustered into three groups, with differences in behavior and risk factors, whereas adherent, non-adherent, and transient adherent patients were identified during the familiarization phase. Regarding the prediction of long-term adherence, the most common DT showed higher performance compared with RF (precision: 80.2 ± 19.5% and 71.8 ± 25.8%, recall: 94.5 ± 14.5% and 71.8 ± 25.8% for DT and RF accordingly). The analysis of the DT rules and the analysis of the feature importance of the RF model highlighted the significance of non-adherence during the familiarization phase, as well as that of the baseline characteristics to predict future adherence. Network analysis revealed different relationships in different clusters of patients and the interplay between their behavioral characteristics. In conclusion, the main novelty of this study is the application of machine learning techniques combining patient characteristics before the start of the home-based CR programs with data during a short familiarization phase, which can predict long-term adherence with high accuracy. The data used in this study are available through connected health technologies and standard measurements in CR; thus, the proposed methodology can be generalized to other telerehabilitation programs and help healthcare providers to improve patient-tailored enrolment strategies and resource allocation.

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Are patient characteristics and modes of delivery associated with completion of cardiac rehabilitation? A national registry analysis

Cited by 8 publications

References 34 publications

The changing landscape of cardiac rehabilitation and the power of personalized therapy

The changing landscape of cardiac rehabilitation and the power of personalized therapy

Evidence of community health workers’ delivery of physical rehabilitation services in sub-Saharan Africa: a scoping review

Predicting Adherence to Home-Based Cardiac Rehabilitation with Data-Driven Methods

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