Projecting the clinical burden of chronic kidney disease at the patient level (Inside CKD): a microsimulation modelling study.

Background: Chronic kidney disease (CKD) is a global concern that presents significant challenges for disease management. Several factors drive CKD prevalence, including primary risk factors, such as type 2 diabetes and hypertension, and an ageing population. Inside CKD is an international initiative that aims to raise awareness of the substantial burden incurred by CKD. Methods: Using a peer-reviewed microsimulation method, the clinical burden of CKD was estimated from 2022 to 2027. Demographic data from the Americas, Europe, and Asia-Pacific/Middle East were used to generate virtual populations and to project the prevalence of CKD, kidney replacement therapy, associated cardiovascular complications, comorbid conditions, and all-cause mortality in the CKD population over the modelled time frame. Findings: Across the 31 participating countries/regions, the total prevalence of CKD was projected to rise to 436.6 million cases by 2027 (an increase of 5.8% from 2022), with most cases (∼80%) undiagnosed. Inside CKD projected a mean of 8859 cases of heart failure, 10,244 of myocardial infarction, and 7797 of stroke per 100,000 patients with CKD by 2027. Interpretation: The clinical impact of CKD is substantial and likely to increase; the high prevalence of undiagnosed cases and associated complications may benefit from the implementation of health policy interventions that promote screening, earlier diagnosis, and interventions to improve outcomes. Funding: AstraZeneca.

A Smart Digital Health Platform to Enable Monitoring of Quality of Life and Frailty in Older Patients with Cancer: A Mixed-Methods, Feasibility Study Protocol.

OBJECTIVES: LifeChamps is an EU Horizon 2020 project that aims to create a digital platform to enable monitoring of health-related quality of life and frailty in patients with cancer over the age of 65. Our primary objective is to assess feasibility, usability, acceptability, fidelity, adherence, and safety parameters when implementing LifeChamps in routine cancer care. Secondary objectives involve evaluating preliminary signals of efficacy and cost-effectiveness indicators. DATA SOURCES: This will be a mixed-methods exploratory project, involving four study sites in Greece, Spain, Sweden, and the United Kingdom. The quantitative component of LifeChamps (single-group, pre-post feasibility study) will integrate digital technologies, home-based motion sensors, self-administered questionnaires, and the electronic health record to (1) enable multimodal, real-world data collection, (2) provide patients with a coaching mobile app interface, and (3) equip healthcare professionals with an interactive, patient-monitoring dashboard. The qualitative component will determine end-user usability and acceptability via end-of-study surveys and interviews. CONCLUSION: The first patient was enrolled in the study in January 2023. Recruitment will be ongoing until the project finishes before the end of 2023. IMPLICATIONS FOR NURSING PRACTICE: LifeChamps provides a comprehensive digital health platform to enable continuous monitoring of frailty indicators and health-related quality of life determinants in geriatric cancer care. Real-world data collection will generate "big data" sets to enable development of predictive algorithms to enable patient risk classification, identification of patients in need for a comprehensive geriatric assessment, and subsequently personalized care.

Impact Assessment of an Innovative Integrated Care Model for Older Complex Patients with Multimorbidity: The CareWell Project.

OBJECTIVES: To evaluate the impact in terms of use of health services, clinical outcomes, functional status, and patient's satisfaction of an integrated care program, the CareWell program, for complex patients with multimorbidity, supported by information and communication technology platforms in six European regions. DATA SOURCES: Primary data were used and the follow-up period ranged between 8 and 12 months. STUDY DESIGN: A quasi-experimental study, targeting chronic patients aged 65 or older, with 2 or more conditions - one of them necessarily being diabetes, congestive heart failure or congestive obstructive pulmonary disease. The intervention group received the integrated care program and the control group received usual care. Generalized mixed regression models were used. DATA COLLECTION: Data were obtained from individual interviews and electronic clinical records. PRINCIPAL FINDINGS: Overall, 856 patients were recruited (475 intervention and 381 control). In the intervention group, the number of visits to emergency rooms was significantly lower, and the number of visits to the general practitioners and primary care nurses was higher than in the control group. CONCLUSION: The CareWell program resulted in improvements in the use of health services, strengthening the role of PC as the cornerstone of care provision for complex patients with multimorbidity.

Economic Evaluation of an Integrated Health and Social Care Program for Heart Failure Through 2 Different Modeling Techniques.

INTRODUCTION: An integrated health and social care program for patients with heart failure (HF) was implemented at the Friuli-Venezia Giulia deployment site as part of the SmartCare European project. The objective of this study was to validate 2 different decision modeling techniques used to perform the economic evaluation. METHODS: Data were collected during the SmartCare project which enrolled 108 patients with HF and followed for more than 6 months. The techniques used were Markov and discrete event simulation models. In both cases, a cost-effectiveness analysis and a budget impact analysis were carried out. The former was used to assign priority to the intervention and the latter to assess its sustainability. Analyses were conducted from the perspective of the Regional Health Authority. RESULTS: Results were similar with both types of model. Cost-effectiveness analysis found no significant differences in quality of life, but the intervention generated significant cost savings, becoming the dominant option. Data extrapolation showed no benefits in terms of mortality or hospital admissions, but budget impact analysis also predicted annual savings, as a significant number of in-hospital days were avoided. In budget analysis, both models predicted early, increasing and cumulative annual savings. DISCUSSION: The integrated program was dominant as it provided better outcomes and lower total costs, and thus, decision-makers should prioritize it. Besides, the work demonstrates the capacity of decision modeling to become a complementary tool in managing integrated health and social care models.