Patient and caregiver reported facilitators of self-care among patients with chronic heart failure: report from a formative qualitative study

Abstract

Background: Adherence to a complex, yet effective medication regimen improves clinical outcomes in patients with chronic heart failure (CHF). However, patient adherence to an agreed upon plan for medication-taking is sub-optimal and continues to hover at 50% in developed countries. Studies to improve medication-taking have focused on interventions to improve adherence to guideline-directed medication therapy, yet few of these studies have integrated patients’ perceptions of what constitutes effective strategies for improved medication-taking and self-care in everyday life. The purpose of this formative study was to explore patient perceived facilitators of selfcare and medication-taking in South Asian CHF patients. Methods: We conducted in-depth interviews of patients with long standing heart failure admitted to the cardiology and internal medicine wards of a South Indian tertiary care hospital. We purposively sampled using the following criteria: sex, socio-economic status, health literacy and patient reported medication adherence in the month prior to hospitalization. We employed inductive coding to identify facilitators. At the end of 15 interviews (eight patients and seven caregivers; seven patient-caregiver dyads), we arrived at theoretical saturation for facilitators. Results: Facilitators could be classified into intrinsic (patient traits – situational awareness, self-efficacy, gratitude, resilience, spiritual invocation and support seeking behavior) and extrinsic (shaped by the environment – financial security and caregiver support, company of children, ease of healthcare access, trust in provider/hospital, supportive environment and recognizing the importance of knowledge). Conclusions: We identified and classified a set of key patient and caregiver reported self-care facilitators among Indian CHF patients. The learnings from this study will be incorporated into an intervention package to improve patient engagement, overall self-care and patient-caregiver-provider dynamics.

A qualitative, grounded theory exploration of the determinants of self-care behavior among Indian patients with a lived experience of chronic heart failure

“…However, since the patient did not have a trusted relationship with any hospital system or a provider, they did not have a clear action plan in the event of symptom exacerbations. This behaviour, representing a negation of trust, may be contrasted by the previously published finding in our facilitators of self-care report, where patients from lower socio-economic strata who had a trustworthy relationship with their physician adhered to long term treatments despite financial constraints [12]. Vesting trust in the healthcare system and in the treating team is thus a pivotal attribute of patients and families who display optimum self-care, among Indian patients.…”

“…As published in an earlier report [ 12 ], we classified factors positively affecting self-care into ‘intrinsic’ (patient traits) and ‘extrinsic’ (external determinants) respectively. Intrinsic traits included situational awareness, self-efficacy, feeling and expressing gratitude, resilience, spiritual invocation and support-seeking behavior.…”

“…Conversely, patients who considered their health as their own responsibility and took the initiative to engage in selfcare displayed, overall, better adherence and selfcare. The presence of children in the household or neighbourhood and utilizing spiritual beliefs are key novel facilitators [ 12 ]. These novel determinants are compatible with the situation-specific theory of decision making in self-care in heart failure [ 17 ].…”

“…The credentials of the investigators who carried out data analysis are detailed in a prior published paper on facilitators of selfcare [ 12 ]. The principal interviewers (KDY and BKB) and data analysts are medically trained doctors with a specialization in clinical pharmacology and a research focus in cardiovascular disease (CVD) prevention.…”

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans

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