Pathways for Enhancing Primary Healthcare Service Capability in China, 2016-2021

Panel data from 30 Chinese provinces covering 2016–2021 analyzes pathways to improve primary healthcare service capability. The study uses a Technology-Organization-Environment framework and Dynamic Qualitative Comparative Analysis to identify configurational pathways and spatiotemporal evolution characteristics. Author Meijiao Wang published this research document under a CC-BY-4.0 license on figshare.

Use Cases

• Analyzing configurational pathways to high service capability based on the TOE-DC theoretical framework.
• Studying the spatiotemporal evolution of healthcare service factors based on panel data from 30 provinces.
• Identifying key conditions like talent pools and economic growth for policy-making based on the QCA results.

Strengths

• Panel data spans 6 years (2016–2021) for longitudinal analysis.
• Analysis covers 30 Chinese provinces, providing a national scope.
• Uses a multi-factor theoretical framework (Technology-Organization-Environment) for analysis.

Limitations

• The dataset is described in a 121.6 KB DOCX file, suggesting limited raw data scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.

Provenance

Source

Meijiao Wang via figshare.

Collection Method

Analysis of panel data using rank-sum ratio (RSR) and Dynamic Qualitative Comparative Analysis (QCA).

Time Range

2016–2021

Freshness

Last updated 2026-04-23 05:35:15; freshness should be verified.

Geography

30 provinces in China, with analysis segmented into eastern, central, and western regions.