Digital Health for Enhanced Understanding and Management of Chronic Conditions: COPD as a Use Case

Roca, Josep; Tényi, Ákos; Cano, Isaac

doi:10.1016/b978-0-12-801238-3.11690-3

Cited by 1 publication

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“…Despite current assessment strategies allow reasonable estimations of patients’ risk, there is room for improvement using multilevel predictive modeling considering as covariates: (i) multimorbidity indices such as adjusted morbidity groups, 22 (ii) clinical information, (iii) patients’ self-tracking data; and (iv) biological markers. 34 , 35 …”

Section: Discussionmentioning

confidence: 99%

“…Despite current assessment strategies allow reasonable estimations of patients' risk, there is room for improvement using multilevel predictive modeling considering as covariates: (i) multimorbidity indices such as adjusted morbidity groups, 22 (ii) clinical information, (iii) patients' self-tracking data; and (iv) biological markers. 34,35 Maturity of Digital Support 19 Digitally supported prehabilitation plays a key enabling role to face some of the identified. Cloud-based digital support, ensuring interoperability between different healthcare providers, constitute a key requirement.…”

Section: Enhanced Risk Assessment and Personalization Of Interventionsmentioning

confidence: 99%

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Actionable Factors Fostering Health Value Generation and Scalability of Prehabilitation

et al. 2022

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Importance: Prehabilitation has potential for improving surgical outcomes as shown in previous randomized controlled trials. However, a marked efficacy-effectiveness gap is limiting its scalability. Comprehensive analyses of deployment of the intervention in real-life scenarios are required. Objective: To assess health outcomes and cost of prehabilitation. Design: Prospective cohort study with a control group built using propensity score–matching techniques. Setting: Prehabilitation Unit in a tertiary-care university hospital. Participants: Candidates for major digestive, cardiac, thoracic, gynecologic, or urologic surgeries. Intervention: Prehabilitation program, including supervised exercise training, promotion of physical activity, nutritional optimization, and psychological support. Main Outcomes and Measures: The comprehensive complication index, hospital and intensive care unit length of stay, and hospital costs per patient until 30 days after surgery. Patients were classified by the degree of program completion and level of surgical aggression for sensitivity analysis. Results: The analysis of the entire study group did not show differences in study outcomes between prehabilitation and control groups (n=328 each). The per-protocol analysis, including only patients completing the program (n=112, 34%), showed a reduction in mean hospital stay [9.9 (7.2) vs 12.8 (12.4) days; P=0.035]. Completers undergoing highly aggressive surgeries (n=60) additionally showed reduction in mean intensive care unit stay [2.3 (2.7) vs 3.8 (4.2) days; P=0.021] and generated mean cost savings per patient of €3092 (32% cost reduction) (P=0.007). Five priority areas for action to enhance service efficiencies were identified. Conclusions and Relevance: The study indicates a low rate of completion of the intervention and identifies priority areas for re-design of service delivery to enhance the effectiveness of prehabilitation.

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Section: Discussionmentioning

confidence: 99%

Section: Enhanced Risk Assessment and Personalization Of Interventionsmentioning

confidence: 99%

Actionable Factors Fostering Health Value Generation and Scalability of Prehabilitation

et al. 2022

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show abstract

Digital Health for Enhanced Understanding and Management of Chronic Conditions: COPD as a Use Case

Cited by 1 publication

References 101 publications

Actionable Factors Fostering Health Value Generation and Scalability of Prehabilitation

Actionable Factors Fostering Health Value Generation and Scalability of Prehabilitation

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