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A cultural and gender-based approach to understanding patient adjustment to chronic heart failure.

ABSTRACT: BACKGROUND:Persons identifying as Black, Chinese, or South Asian make up the largest minority groups in Canada. Individuals with chronic heart failure (CHF) from these groups experience a greater rate of re-hospitalization and poorer quality of life. Although experts agree that culture can shape the experience of CHF, little is known about how patients from these minority populations define a good quality of life with CHF and what barriers they experience when carrying out self-care behaviours. The aim of this qualitative study was to examine cultural and gender-based influences on quality of life in patients with CHF. METHODS:Purposive sampling included 30 patients (67% male), 18 to 75?years of age, who self-identified as Black (n?=?8), Chinese (n?=?9), or South Asian (n?=?6). Caucasians (n?=?7) were included as a comparison group. Semi-structured interviews (see the online appendix), lasting approximately 60?min, were conducted, which focused on personal understanding of CHF and living with the disease, including impact on lifestyle and quality of life. An inductive qualitative approach with thematic content analysis was used to develop key insights into individual experience of CHF, as well as cultural and gender-based influences on self-care and quality of life. Descriptive statistics were generated from questionnaire responses. RESULTS:Five key themes emerged from the narrative analysis of participant interviews: (i) CHF as an emergent reality, (ii) quality of life and disruption of lifecourse milestones, (iii) the challenge to accept CHF and re-evaluation of quality of life; (iv) impact on social activities essential to quality of life, and (v) life with CHF as a commitment to culturally tailored self-care. Participants described the unique impact of CHF on their quality of life, including life trajectory milestones such as dating, parenting, and retirement planning, as well as the importance of accepting their diagnosis, and the reframing goals for living well with heart failure. Positive and negative impacts on social relationships were noted, including sexual intimacy and interactions with spouses, other family members, and co-workers. CONCLUSIONS:Study findings highlight important lifespan, cultural, and gender considerations that can inform the improvement of patient care and quality of life for patients and their families.

SUBMITTER: Surikova J

PROVIDER: S-EPMC7368735 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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A cultural and gender-based approach to understanding patient adjustment to chronic heart failure.

Surikova Jelena J Payne Ada A Miller Karen-Lee KL Ravaei Arian A Nolan Robert P RP

Health and quality of life outcomes 20200718 1

<h4>Background</h4>Persons identifying as Black, Chinese, or South Asian make up the largest minority groups in Canada. Individuals with chronic heart failure (CHF) from these groups experience a greater rate of re-hospitalization and poorer quality of life. Although experts agree that culture can shape the experience of CHF, little is known about how patients from these minority populations define a good quality of life with CHF and what barriers they experience when carrying out self-care beha ...[more]

PMID: 32682424

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Project description:BackgroundPatient-reported outcomes (PROs) can be obtained outside hospitals and are of great significance for evaluation of patients with chronic heart failure (CHF). The aim of this study was to establish a prediction model using PROs for out-of-hospital patients.MethodsCHF-PRO were collected in 941 patients with CHF from a prospective cohort. Primary endpoints were all-cause mortality, HF hospitalization, and major adverse cardiovascular events (MACEs). To establish prognosis models during the two years follow-up, six machine learning methods were used, including logistic regression, random forest classifier, extreme gradient boosting (XGBoost), light gradient boosting machine, naive bayes, and multilayer perceptron. Models were established in four steps, namely, using general information as predictors, using four domains of CHF-PRO, using both of them and adjusting the parameters. The discrimination and calibration were then estimated. Further analyze were performed for the best model. The top prediction variables were further assessed. The Shapley additive explanations (SHAP) method was used to explain black boxes of the models. Moreover, a self-made web-based risk calculator was established to facilitate the clinical application.ResultsCHF-PRO showed strong prediction value and improved the performance of the models. Among the approaches, XGBoost of the parameter adjustment model had the highest prediction performance with an area under the curve of 0.754 (95% CI: 0.737 to 0.761) for death, 0.718 (95% CI: 0.717 to 0.721) for HF rehospitalization and 0.670 (95% CI: 0.595 to 0.710) for MACEs. The four domains of CHF-PRO, especially the physical domain, showed the most significant impact on the prediction of outcomes.ConclusionCHF-PRO showed strong prediction value in the models. The XGBoost models using variables based on CHF-PRO and the patient's general information provide prognostic assessment for patients with CHF. The self-made web-based risk calculator can be conveniently used to predict the prognosis for patients after discharge.Clinical trial registrationURL: http://www.chictr.org.cn/index.aspx ; Unique identifier: ChiCTR2100043337.

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:BackgroundReduction of 30-day all-cause readmissions for heart failure (HF) has become an important quality-of-care metric for health care systems. Many hospitals have implemented quality improvement programs designed to reduce 30-day all-cause readmissions for HF. Electronic medical record (EMR)-based measures have been employed to aid in these efforts, but their use has been largely adjunctive to, rather than integrated with, the overall effort.ObjectivesWe hypothesized that a comprehensive EMR-based approach utilizing an HF dashboard in addition to an established HF readmission reduction program would further reduce 30-day all-cause index hospital readmission rates for HF.MethodsAfter establishing a quality improvement program to reduce 30-day HF readmission rates, we instituted EMR-based measures designed to improve cohort identification, intervention tracking, and readmission analysis, the latter 2 supported by an electronic HF dashboard. Our primary outcome measure was the 30-day index hospital readmission rate for HF, with secondary measures including the accuracy of identification of patients with HF and the percentage of patients receiving interventions designed to reduce all-cause readmissions for HF.ResultsThe HF dashboard facilitated improved penetration of our interventions and reduced readmission rates by allowing the clinical team to easily identify cohorts with high readmission rates and/or low intervention rates. We significantly reduced 30-day index hospital all-cause HF readmission rates from 18.2% at baseline to 14% after implementation of our quality improvement program ( P = .045). Implementation of our EMR-based approach further significantly reduced 30-day index hospital readmission rates for HF to 10.1% ( P for trend = .0001). Daily time to screen patients decreased from 1 hour to 15 minutes, accuracy of cohort identification improved from 83% to 94.6% ( P = .0001), and the percentage of patients receiving our interventions, such as patient education, also improved significantly from 22% to 100% over time ( P < .0001).ConclusionsIn an institution with a quality improvement program already in place to reduce 30-day readmission rates for HF, an EMR-based approach further significantly reduced 30-day index hospital readmission rates.

Dataset Information

A cultural and gender-based approach to understanding patient adjustment to chronic heart failure.

Publications

A cultural and gender-based approach to understanding patient adjustment to chronic heart failure.

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