Relationship between quality management and organizational performance in the healthcare industry

Heng Xie, Xinyu Wei, Xianghui Peng, Victor Prybutok

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates how Quality Management (QM) programmes, particularly the Baldrige excellence framework, provide an approach to enhance healthcare organisational performance. Two independent methods were used to examine the short-term and long-term effects of winning the Baldrige award and the specific influence of common QM practices on results. The first method assesses the Baldrige Award’s impact on hospital performance by examining patient survey data and shows that initial quality improvements are not sustained in the long term. The second method uses confirmatory semantic analysis (CSA), a text-mining method, to analyse 22 Baldrige award-winning applications to determine the relationship between QM practices and organisational results in healthcare settings. The results show that only three QM practices–measurement, analysis, and knowledge management (MAKM), leadership, and operations focus–significantly contribute to organisational performance. Furthermore, CSA findings highlight the dominant role of leadership in driving performance outcomes, with other factors in the framework showing nonsignificant mediation effects. By exploring both the overarching effectiveness of QM programmes across different time lengths and specific practices that contribute to performance, this research provides academic insights with practical application in the healthcare industry. Importantly, the findings highlight the nuanced relationship between QM initiatives and organisational excellence.

Original languageEnglish (US)
Pages (from-to)8518-8536
Number of pages19
JournalInternational Journal of Production Research
Volume62
Issue number23
DOIs
StatePublished - 2024

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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