Gender and caste inequalities in primary healthcare usage by under-5 children in rural Nepal: an iterative qualitative study into provider perspectives and the potential role of implicit bias.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 37369413.
- Also identified by DOI 10.1136/bmjopen-2022-069060 and PMC identifier 10410982.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
This study explored provider perspectives on: (1) why inequalities in health service usage persist; and (2) their knowledge and understanding of the role of patient experience and implicit bias (also referred to as unconscious bias). A three stage, iterative qualitative study was conducted involving two rounds of in-depth interviews and a training session with healthcare staff. Interview transcripts were analysed using a reflexive thematic approach in relation to the study's aims. Participants were recruited from rural hill districts (Mugu, Humla, Bajura, Gorkha and Sindhupalchok) of Nepal. Clinical staff from 22 rural health posts. Healthcare providers had high levels of understanding of the cultural, educational and socioeconomic factors behind inequalities in healthcare usage in their communities. However, there was less knowledge and understanding of the role of patient experience-and no recognition at all of the concept of implicit bias. It is highly likely that implicit bias affects provider behaviours in Nepal, just as it does in other countries. However, there is currently not a culture of thinking about the patient experience and how that might impact on future usage of health services. Implicit bias training for health students and workers would help create greater awareness of unintended discriminatory behaviours. This in turn may play a part in improving patient experience and future healthcare usage, particularly among disadvantaged groups.
Medical subject headings
- Bias, Implicit
- Social Class