JOURNAL ARTICLE

The Impact of Healthcare Delivery Complexity on Practices for Clinical Quality Improvement: A Case of Healthcare Workers' Hand Hygiene Compliance.

  • Published In: Service Science (INFORMS), 2023, v. 15, n. 4. P. 283 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Chen, Wenlin; Tseng, Chung-Li; Tseng, Cynthia 3 of 3

Abstract

This article examines how healthcare delivery complexity influences the effectiveness of quality improvement (QI) practices on clinical quality, measured by healthcare workers' (HCWs) adherence to standardized hand hygiene processes. Using discrete choice experiments with 320 nurses at a Taiwanese university hospital, the study identifies two types of complexity: contextual complexity (patient risk and hand contamination risk) and provider complexity (heterogeneous HCW attitudes and characteristics). Results show that contextual complexity affects the degree of QI practice effectiveness, while provider complexity determines whether a QI practice is effective, revealing three distinct HCW classes with differing responses to approach-based (e.g., easy access to resources) and avoidance-based (e.g., intergroup competition, posting individual performance) QI practices. The findings suggest that combining both approach- and avoidance-based QI practices, tailored to the heterogeneous provider profiles and contextual risks, can better improve clinical quality, highlighting the need for customized interventions within healthcare settings.

Additional Information

  • Source:Service Science (INFORMS). 2023/12, Vol. 15, Issue 4, p283
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:2164-3962
  • DOI:10.1287/serv.2023.0323
  • Accession Number:174199560
  • Copyright Statement:Copyright of Service Science (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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