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Data from: Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care

Citation

Engl, Elisabeth et al. (2019), Data from: Categorizing and assessing comprehensive drivers of provider behavior for optimizing quality of health care, Dryad, Dataset, https://doi.org/10.5061/dryad.6974t14

Abstract

Inadequate quality of care in healthcare facilities is one of the primary causes of patient mortality in low- and middle-income countries, and understanding the behavior of healthcare providers is key to addressing it. Much of the existing research concentrates on improving resource-focused issues, such as staffing or training, but these interventions do not fully close the gaps in quality of care. By contrast, there is a lack of knowledge regarding the full contextual and internal drivers–such as social norms, beliefs, and emotions–that influence the clinical behaviors of healthcare providers. We aimed to provide two conceptual frameworks to identify such drivers, and investigate them in a facility setting where inadequate quality of care is pronounced. Using immersion interviews and a novel decision-making game incorporating concepts from behavioral science, we systematically and qualitatively identified an extensive set of contextual and internal behavioral drivers in staff nurses working in reproductive, maternal, newborn, and child health (RMNCH) in government public health facilities in Uttar Pradesh, India. We found that the nurses operate in an environment of stress, blame, and lack of control, which appears to influence their perception of their role as often significantly different from the RMNCH program’s perspective. That context influences their perceptions of risk for themselves and for their patients, as well as self-efficacy beliefs, which could lead to avoidance of responsibility, or incorrect care. A limitation of the study is its use of only qualitative methods, which provide depth, rather than prevalence estimates of findings. This exploratory study identified previously under-researched contextual and internal drivers influencing the care-related behavior of staff nurses in public facilities in Uttar Pradesh. We recommend four types of interventions to close the gap between actual and target behaviors: structural improvements, systemic changes, community-level shifts, and interventions within healthcare facilities.

Usage Notes

Facility decision making scores_aggregate

Full 17 decision making games scenarios with aggregate responses chosen by health facility staff in Uttar Pradesh, India.

Facility decision making transcripts_anon

Qualitative transcripts from post-decision making game interviews of health facility staff in Uttar Pradesh, India.

Immersions_anon

Qualitative transcripts from in-facility immersion interviews of health facility staff in Uttar Pradesh, India.