Patient non-adherence: an interpretative phenomenological analysis.

Purpose While interpretative phenomenological analysis (IPA) has been used in health psychology research, it has so far not been applied to seek deeper insights into the patients' experiences about treatment. The purpose of this paper is to address this gap by using IPA to understand patient non-adherence. Design/methodology/approach In total, 18 patients with chronic conditions seeking healthcare services in Goa and Karnataka, India, were selected by using the snowball sampling method. In-depth interviews were conducted face to face. A semi-structured questionnaire developed by the researchers was used to collect the data. IPA was used to explore the themes to predict patient non-adherence. Findings The study results indicate that economic factors, health system related factors, social factors and psychological factors impact patient non-adherence. Patient non-adherence includes medication non-adherence and lifestyle modification non-adherence. Research limitations/implications Being cross sectional in design, the results may not be as appropriate as the results derived from a longitudinal study given that non-adherence occurs over time. Practical implications Patient non-adherence is a global health issue. Multidisciplinary approach to enhance patient adherence to treatment should form part of public healthcare policy. Social implications Exploring the factors influencing patient non-adherence will help the health-care industry stakeholders to reduce healthcare cost and improve patient's quality of life. Originality/value Although there is extensive quantitative research on the prevalence of non-adherence, qualitative research is limited. This paper addresses this gap by using IPA to understand patient non-adherence and its factors and dimensions.

Service quality in the public sector hospitals: a study in India.

Most studies on service quality have been conducted in the context of the private sector of the economy. In fact, in the healthcare setting, for a long time, public-sector hospitals were not expected to excel in the provision of service quality. In a country such as India, even now, public-sector hospital staffs enjoy relatively higher salaries, flexible work schedules, and secure employment until retirement. Because patients do not pay for most services, normally they are concerned only about the quality of the core product. The authors indicate that, even in the public sector context, the quality of the physician and that of the clinical support staff significantly impact patient satisfaction. However, the quality of nonclinical support staff is not found to have any significant effect on patient satisfaction.

Regimen Difficulty and Medication Non-Adherence and the Interaction Effects of Gender and Age.

Medication non-adherence is a global health issue. Numerous factors predict it. This study is aimed to identify the association between regimen difficulty and medication non-adherence among patients with chronic conditions and testing the interaction effects of gender and age on the same. It was a cross-sectional study conducted among 479 outpatients from India. Convenience sampling method was used. Multiple regression analyses were performed to find the predictors of non-adherence and to test interaction effects. Regimen difficulty predicted medication non-adherence. The patient's gender and age have interaction effects on the relationship between regimen difficulty and medication non-adherence.

Does Quality of Healthcare Service Determine Patient Adherence? Evidence from the Primary Healthcare Sector in India.

Patient adherence is extremely important to achieve positive outcome. While quality of healthcare service has been studied as a determinant of patient satisfaction and loyalty, its impact on patient adherence has not been examined. The authors attempt to determine dimensions of quality and their impact on patient adherence in primary healthcare in India. Exploratory factor analysis resulted into seven factors. Factor scores were used for regression to identify the influence of dimensions of service quality on patient adherence. Quality of healthcare emerged as a determinant of patient adherence.