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All Journal JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi)
Kilis, Filly Elisabeth
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Decision Sciences, Operations Research & Management

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PENGARUH NURSE BURNOUT TERHADAP QUALITY OF PATIENT CARE DAN KEJADIAN ADVERSE EVENTS YANG DIMEDIASI OLEH WORK ENGAGEMENT (STUDI PADA TIGA RUMAH SAKIT SWASTA) Kilis, Filly Elisabeth; Achmadi, Hendra
JMBI UNSRAT (Jurnal Ilmiah Manajemen Bisnis dan Inovasi Universitas Sam Ratulangi). Vol 11 No 3 (2024): JMBI UNSRAT Volume 11 Nomor 3
Publisher : FEB Universitas Sam Ratulangi Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35794/jmbi.v11i3.59165

Abstract

Burnout is a condition of exhaustion that includes physical, emotional, and mental aspects due to prolonged stress in the nursing profession. High workload, significant emotional distress, and lack of institutional support can trigger this condition. Study aims to evaluate the effect of nurse burnout on the quality of patient care and adverse events in a hospital, by considering the role of work engagement as a mediator. Background of this study is based on the increase in patient safety incidents as well as the high turnover rate of nurses over the period 2022 to 2024, which reflects significant challenges in the healthcare system and its potential impact on quality of care. A quantitative approach with a cross-sectional research design and sample data in this study was taken using non-probability sampling method, by purposive sampling obtained from nurses in three private hospitals using a questionnaire. There were 282 eligible samples and analyzed with PLS-SEM. Results show the model explained 21.6% of the variation in adverse event occurrence (R² = 0.216), 39.3% of quality of patient care (R² = 0.393), and 2.6% of work engagement (R² = 0.026). A moderate predictive ability was found for adverse events (Q² = 0.168), while quality of patient care (Q² = 0.022) and work engagement (Q² = 0.016) were moderately predictive. CVPAT of this study shows that the PLS-SEM model has better predictive ability compared to the indicator average (IA) and linear model (LM) (negative ALD value and p-value ≤ 0.05) which indicates adequate predictive ability.
Co-Authors Hendra Achmadi, Hendra