Mapping the barriers of effective healthcare service quality using expert mining and ISM–MICMAC approach

Abstract

Purpose This analysis aims to determine and prioritise the barriers of effective healthcare service quality (EHSQ) in an emerging economy by deploying an integrated expert mining and interpretive structural modelling cross-impact matrix multiplication applied to a classification (MICMAC) method. Design/methodology/approach This analysis uses a unified method in two parts. In the first part, a structured literature analysis and an expert mining tool have been used to identify and validate the EHSQ barrier. In the subsequent part, an interpretive structural modeling (ISM) has been used to examine the interrelationships among EHSQ barriers to determine a structural model. Subsequently, the MICMAC approach has been deployed to categorise the EHSQ barriers based on their driver and dependence power. Findings This analysis recognised 11 key barriers of EHSQ in an emerging economy and created a hierarchical framework using ISM. Furthermore, EHSQ barriers have been classified into four clusters using the MICMAC approach. In the framework, societal-related EHSQ barriers are primarily at the highest level, operational barriers at the mid-level and service quality-related EHSQ barriers at the bottommost level. Research limitations/implications Results are valuable for strategists in better health governance of an EHSQ. Practical implications The outcomes deliver significant insight for healthcare policymakers to understand the contextual relationships among EHSQ barriers and assist in formulating strategies to abolish the leading EHSQ barriers. Social implications This study’s outcomes are helpful for public health planners to develop an appropriate health policy by removing EHSQ barriers. Originality/value This study first prioritised the EHSQ barriers by integrating ISM–MICMAC.