# Analysis of healthcare resource allocation efficiency and improvement pathways in Guangxi based on fsQCA configuration perspective

## TL;DR

This study examines healthcare resource efficiency in Guangxi, China, using a mixed-methods approach to identify factors influencing allocation disparities and suggest improvement strategies.

## Contribution

The study introduces a configurational analysis of healthcare efficiency using fsQCA, revealing multiple pathways and causal asymmetry in resource allocation.

## Key findings

- Healthcare resource allocation efficiency in Guangxi is suboptimal with a mean score of 0.364 and significant regional disparities.
- Four configurations of high efficiency and seven of low efficiency were identified, highlighting the role of socioeconomic development and government support.
- Ethnic minority areas show vulnerability due to unfavorable condition profiles, suggesting the need for tailored, place-based policies.

## Abstract

Disparities in healthcare resource allocation present a significant challenge in China, particularly in underdeveloped western regions like Guangxi. Moving beyond analyses of isolated factors, this study investigates the complex, synergistic interactions of socioeconomic, governmental, and demand-side conditions that shape allocation efficiency.

We employed a two-stage, mixed-methods approach. First, Data Envelopment Analysis (DEA) evaluated the relative efficiency of 14 prefecture-level cities in Guangxi, using healthcare personnel and hospital beds as inputs, and outpatient visits and hospital discharges as outputs. Second, Fuzzy-Set Qualitative Comparative Analysis (fsQCA) was used to identify configurations of conditions (including per capita GDP, urbanization, government expenditure, and per capita health spending) leading to high or low efficiency.

The overall efficiency of healthcare resource allocation in Guangxi was suboptimal (mean score: 0.364), with significant regional disparities. The fsQCA revealed multiple, equifinal pathways to outcomes, demonstrating causal asymmetry. We identified four configurations for high efficiency (solution consistency: 0.809; coverage: 0.771), where robust socioeconomic development (per capita GDP, urbanization) was a core condition in most paths. Conversely, seven configurations led to low efficiency (solution consistency: 0.876; coverage: 0.733), often characterized by insufficient government support or socioeconomic development, even when other factors like health demand were high.

Our findings indicate that healthcare resource allocation efficiency is shaped by the synergistic interaction of multiple conditions rather than any single factor. This configurational perspective explains the stark regional disparities, with ethnic minority areas being particularly vulnerable due to unfavorable condition profiles. We recommend tailored, place-based policies, such as strengthening primary care, promoting “Internet + Healthcare,” and establishing regional medical centers, to create synergistic effects and optimize resource allocation.