Multi-state modelling of heart failure care path: A population-based investigation from Italy

Abstract

BackgroundHow different risk profiles of heart failure (HF) patients can influence multiple readmissions and outpatient management is largely unknown. We propose the application of two multi-state models in real world setting to jointly evaluate the impact of different risk factors on multiple hospital admissions, Integrated Home Care (IHC) activations, Intermediate Care Unit (ICU) admissions and death.Methods and findingsThe first model (model 1) concerns only hospitalizations as possible events and aims at detecting the determinants of repeated hospitalizations. The second model (model 2) considers both hospitalizations and ICU/IHC events and aims at evaluating which profiles are associated with transitions in intermediate care with respect to repeated hospitalizations or death. Both are characterized by transition specific covariates, adjusting for risk factors. We identified 4,904 patients (4,129 de novo and 775 worsening heart failure, WHF) hospitalized for HF from 2009 to 2014. 2,714 (55%) patients died. Advanced age and higher morbidity load increased the rate of dying and of being rehospitalized (model 1), decreased the rate of being discharged from hospital (models 1 and 2) and increased the rate of inactivation of IHC (model 2). WHF was an important risk factor associated with hospital readmission.ConclusionMulti-state models enable a better identification of two patterns of HF patients. Once adjusted for age and comorbidity load, the WHF condition identifies patients who are more likely to be readmitted to hospital, but does not represent an increasing risk factor for activating ICU/IHC. This highlights different ways to manage specific patients’ patterns of care. These results provide useful healthcare support to patients’ management in real world context. Our study suggests that the epidemiology of the considered clinical characteristics is more nuanced than traditionally presented through a single event.

Statistical Challenges of Administrative and Transaction Data

“…Accessibility is a crucial issue for public health data (Schneeweiss, 2014) due to the different legal constraints and protocols that (whether they) exist. However, to ensure the accuracy of the information, a twofold strategy may be pursued: to link administrative data with suitable clinical registries or surveys (Gasperoni et al, 2017) and to check appropriateness of clinical questions that may be answered by these data, since 'the quality is not a property of the data set itself' but depends on the 'use to which it is put'. As an example, specific guidelines for dealing with administrative databases when acute and/or chronic cardiovascular diseases are considered are provided in Gasperoni et al (2017), Barbieri et al (2010), Mazzali et al (2016) and Ieva et al (2015).…”

“…As an example, specific guidelines for dealing with administrative databases when acute and/or chronic cardiovascular diseases are considered are provided in Gasperoni et al . (), Barbieri et al . (), Mazzali et al .…”

Health Related Quality of Life Among Heart Failure Patients Attending an Outpatient Clinic at University of Gondar Comprehensive Specialized Hospital Northwest Ethiopia 2020: Structural Equation Modeling Approach

“…Maximizing HRQOL among treating CHF is still a major challenge (15)(16)(17)(18). In primary care, CHF patients are in need of new concepts adapted to the severity of their disease that consider life expectancy and HRQOL.…”

Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model

“…HF is typical of chronic syndromes affecting elderly populations, and confers high risk of hospital readmission and death; both outcomes are clinically important and indicative of provider performance [16]. The work builds on a small number of previous studies that have provided a more complete analysis of the clinical pathway of HF patients [17][18][19][20].…”