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

ABSTRACT: 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.

SUBMITTER: Larranaga I

PROVIDER: S-EPMC6287322 | biostudies-literature | 2018 Jan-Dec

REPOSITORIES: biostudies-literature

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

Larrañaga Igor I Stafylas Panos P Fullaondo Ane A Apuzzo Gian Matteo GM Mar Javier J

Health services research and managerial epidemiology 20180101

<h4>Introduction</h4>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.<h4>Methods</h4>Data were collected during the SmartCare project which enrolled 108 patients with HF and followed for more than 6 months. The techniques used were Marko ...[more]

PMID: 30547054

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Project description:ImportancePrompted by null findings from several care transition trials and practice changes for heart failure in recent years, leaders from a large integrated health care system aimed to reassess the outcomes of its 10-year multicomponent transitional care program for heart failure (HF-TCP).ObjectiveTo examine the association of the individual HF-TCP components and their bundle with the primary outcome of all-cause 30-day inpatient or observation stay readmissions.Design, setting, and participantsThis retrospective cohort study included patients enrolled in the HF-TCP during an inpatient encounter for heart failure at 13 Kaiser Permanente Southern California hospitals from January 1, 2013, to October 31, 2018, who were followed up from discharge until 30 days, readmission, or death. Data were analyzed from May 7, 2019, to May 1, 2020, with additional review from September 2 to October 1, 2020.ExposuresPatients received 1 home health visit or telecare (telephone) visit from a registered nurse within 2 days of hospital discharge, a heart failure care manager call within 7 days, and a clinic visit with a physician or a nurse practitioner within 7 days.Main outcomes and measuresMultivariable proportional hazards regression models were used to estimate the probability of 30-day readmission for those who received the individual or bundled HF-TCP components compared with those who did not.ResultsA total of 26 128 patients were included; 57.0% were male, and the mean (SD) age was 73 (13) years. The 30-day readmission rate was 18.1%. Both exposure to a home health visit within 2 days of discharge (hazard ratio [HR], 1.03; 95% CI, 0.96-1.10) and a 7-day heart failure case manager call (HR, 1.08; 95% CI, 0.99-1.18) compared with no visit or call were not associated with a lower rate of readmission. Completion of a 7-day clinic visit was associated with a lower readmission rate (HR, 0.88; 95% CI, 0.81-0.94) compared with no clinic visit. There were no synergistic effects of all 3 components compared with clinic visit alone (HR, 1.05; 95% CI, 0.87-1.28).Conclusions and relevanceThis study found that HF-TCP as a whole was not associated with a reduction in 30-day readmission rates, although a follow-up clinic visit within 7 days of discharge may be helpful. These findings highlight the importance of continuous quality improvement and refinement of existing clinical programs.

Project description:BackgroundThe management of heart failure (HF) is challenging because of the complexities in recommended therapies. Integrated disease management (IDM) is an effective model, promoting guideline-directed care, but the impact of IDM in the community setting requires further evaluation.MethodsA retrospective evaluation of community-based IDM. Patient characteristics were described, and outcomes using a pre- and post-intervention design were HF-related health-service use, quality of life, and concordance with guideline-directed medical therapy (GDMT).Results715 patients were treated in the program (2016 to 2023), 219 in a community specialist-care clinic, and 496 in 25 primary-care clinics. The overall cohort was predominantly male (60%), with a mean age of 73.5 years (± 10.7), and 60% with HF with reduced ejection fraction. In patients with ≥ 6 months of follow-up (n = 267), pre vs post annualized rates of HF-related acute health-service use decreased from 36.3 to 8.5 hospitalizations per 100 patients per year, P < 0.0001, from 31.8 to 13.1 emergency department visits per 100 patients per year, P < 0.0001, and from 152.8 to 110.0 urgent physician visits per 100 patients per year, P = 0.0001. The level of concordance with GDMT improved; the number of patients receiving triple therapy and quadruple therapy increased by 10.1% (95% confidence interval [CI], 2.4%,17.8%) and 19.6% (95% CI, 12.0%, 27.3%), respectively. Within these groups, optimal dosing was achieved in 42.5% (95% CI, 32.0%, 53.6%) and 35.0% (95% CI, 23.1%, 48.4%), respectively. In patients with at least one follow-up visit (n = 286), > 50% experienced a clinically relevant improvement in their quality of life.ConclusionsA community-based IDM program for HF, may reduce HF-related acute health-service use, improve quality of life and level of concordance with GDMT. These encouraging preliminary outcomes from a real-world program evaluation require confirmation in a randomized controlled trial.

Project description:BackgroundHeart failure (HF) is a multifaceted clinical syndrome characterized by different etiologies, risk factors, comorbidities, and a heterogeneous clinical course. The current model, based on data from clinical trials, is limited by the biases related to a highly-selected sample in a protected environment, constraining the applicability of evidence in the real-world scenario. If properly leveraged, the enormous amount of data from real-world may have a groundbreaking impact on clinical care pathways. We present, here, the development of an HF DataMart framework for the management of clinical and research processes.MethodsWithin our institution, Fondazione Policlinico Universitario A. Gemelli in Rome (Italy), a digital platform dedicated to HF patients has been envisioned (GENERATOR HF DataMart), based on two building blocks: 1. All retrospective information has been integrated into a multimodal, longitudinal data repository, providing in one single place the description of individual patients with drill-down functionalities in multiple dimensions. This functionality might allow investigators to dynamically filter subsets of patient populations characterized by demographic characteristics, biomarkers, comorbidities, and clinical events (e.g., re-hospitalization), enabling agile analyses of the outcomes by subsets of patients. 2. With respect to expected long-term health status and response to treatments, the use of the disease trajectory toolset and predictive models for the evolution of HF has been implemented. The methodological scaffolding has been constructed in respect of a set of the preferred standards recommended by the CODE-EHR framework.ResultsSeveral examples of GENERATOR HF DataMart utilization are presented as follows: to select a specific retrospective cohort of HF patients within a particular period, along with their clinical and laboratory data, to explore multiple associations between clinical and laboratory data, as well as to identify a potential cohort for enrollment in future studies; to create a multi-parametric predictive models of early re-hospitalization after discharge; to cluster patients according to their ejection fraction (EF) variation, investigating its potential impact on hospital admissions.ConclusionThe GENERATOR HF DataMart has been developed to exploit a large amount of data from patients with HF from our institution and generate evidence from real-world data. The two components of the HF platform might provide the infrastructural basis for a combined patient support program dedicated to continuous monitoring and remote care, assisting patients, caregivers, and healthcare professionals.

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

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

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