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Ahmed FZ, Sammut-Powell C, Martin GP, Callan P, Cunnington C, Kahn M, Kale M, Weldon T, Harwood R, Fullwood C, Gerritse B, Lanctin D, Soken N, Campbell NG, Taylor JK. Association of a device-based remote management heart failure pathway with outcomes: TriageHF Plus real-world evaluation. ESC Heart Fail 2024. [PMID: 38712903 DOI: 10.1002/ehf2.14821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/08/2024] [Accepted: 04/02/2024] [Indexed: 05/08/2024] Open
Abstract
AIMS Clinical pathways have been shown to improve outcomes in patients with heart failure (HF). Although patients with HF often have a cardiac implantable electronic device, few studies have reported the utility of device-derived risk scores to augment and organize care. TriageHF Plus is a device-based HF clinical pathway (DHFP) that uses remote monitoring alerts to trigger structured telephone assessment for HF stability and optimization. We aimed to evaluate the impact of TriageHF Plus on hospitalizations and describe the associated workforce burden. METHODS AND RESULTS TriageHF Plus was a multi-site, prospective study that compared outcomes for patients recruited between April 2019 and February 2021. All alert-triggered assessments were analysed to determine the appropriateness of the alert and the workload burden. A negative-binomial regression with inverse probability treatment weighting using a time-matched usual care cohort was applied to estimate the effect of TriageHF Plus on non-elective hospitalizations. A post hoc pre-COVID-19 sensitivity analysis was also performed. The TriageHF Plus cohort (n = 443) had a mean age of 68.8 ± 11.2 years, 77% male (usual care cohort: n = 315, mean age of 66.2 ± 14.5 years, 65% male). In the TriageHF Plus cohort, an acute medical issue was identified following an alert in 79/182 (43%) cases. Fifty assessments indicated acute HF, requiring clinical action in 44 cases. At 30 day follow-up, 39/66 (59%) of initially symptomatic patients reported improvement, and 20 (19%) initially asymptomatic patients had developed new symptoms. On average, each assessment took 10 min. The TriageHF Plus group had a 58% lower rate of hospitalizations across full follow-up [incidence relative ratio: 0.42, 95% confidence interval (CI): 0.23-0.76, P = 0.004]. Across the pre-COVID-19 window, hospitalizations were 31% lower (0.69, 95% CI: 0.46-1.04, P = 0.077). CONCLUSIONS These data represent the largest real-world evaluation of a DHFP based on multi-parametric risk stratification. The TriageHF Plus clinical pathway was associated with an improvement in HF symptoms and reduced all-cause hospitalizations.
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Affiliation(s)
- Fozia Zahir Ahmed
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Camilla Sammut-Powell
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Glen P Martin
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Paul Callan
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Colin Cunnington
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Matthew Kahn
- Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, UK
| | - Mita Kale
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Toni Weldon
- Department of Cardiology, Northern Care Alliance NHS Foundation Trust, Manchester, UK
| | - Rachel Harwood
- Statistics Department, Research and Innovation, Manchester University NHS Foundation Trust, Manchester, UK
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Catherine Fullwood
- Statistics Department, Research and Innovation, Manchester University NHS Foundation Trust, Manchester, UK
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | | | | | | | - Niall G Campbell
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Joanne K Taylor
- Department of Cardiology, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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Iyngkaran P, Usmani W, Hanna F, de Courten M. Challenges of Health Data Use in Multidisciplinary Chronic Disease Care: Perspective from Heart Failure Care. J Cardiovasc Dev Dis 2023; 10:486. [PMID: 38132654 PMCID: PMC10743507 DOI: 10.3390/jcdd10120486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 11/13/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023] Open
Abstract
The healthcare sector generates approximately 30% of all the world's data volume, mostly for record keeping, compliance and regulatory requirements, and patient care. Healthcare data often exist in silos or on different systems and platforms due to decentralised storage and data protection laws, limiting accessibility for health service research. Thus, both the lack of access to data and more importantly the inability to control data quality and explore post-trial (phase IV) data or data with translational relevance have an impact on optimising care and research of congestive heart failure (CHF). We highlight that for some diseases, such as CHF, generating non-traditional data has significant importance, but is hindered by the logistics of accessing chronic disease data from separate health silos and by various levels of data quality. Modern multidisciplinary healthcare management of cardiovascular diseases-especially when spanning across community hubs to tertiary healthcare centres-increases the complexities involved between data privacy and access to data for healthcare and health service research. We call for an increased ability to leverage health data across systems, devices, and countries.
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Affiliation(s)
- Pupalan Iyngkaran
- Department of Health Sciences, Torrens University Australia, Melbourne 3000, Australia;
| | - Wania Usmani
- Department of Health Sciences, Torrens University Australia, Melbourne 3000, Australia;
| | - Fahad Hanna
- Public Health Program, Department of Health and Education, Torrens University Australia, Melbourne 3000, Australia;
| | - Maximilian de Courten
- Mitchell Institute for Health and Education Policy, Victoria University, Melbourne 3000, Australia;
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