Development of a Life Cycle Cost Analysis Model for Mortuary Buildings to Enhance Availability Performance: The Case Study of Musoma Municipal Council Hospital

Healthcare facilities require comprehensive maintenance management strategies to ensure optimal service delivery and operational efficiency. This study developed a life cycle cost analysis (LCCA) model to improve maintenance management and availability performance of mortuary buildings, using Musoma Municipal Council Hospital as a case study. A mixed-methods research approach was adopted, involving comprehensive field observations, structured interviews, and systematic surveys with 36 participants representing diverse stakeholders, including engineers, administrators, technicians, mortuary staff, and healthcare professionals. Twelve technical factors influencing maintenance costs were systematically analysed using the Relative Importance Index (RII) methodology to establish priority rankings based on professional expertise and operational experience. The analysis revealed that electrical systems' reliability and backup power emerged as the most critical factor (RII = 0.931), followed by environmental control for chemical storage (RII = 0.923), and infection control and biosafety features (RII = 0.915). A robust multiple regression model was subsequently formulated using the seven highest-ranked factors, producing strong predictive outcomes with R² = 0.780, indicating that 78% of the variance in availability performance could be explained by the identified technical factors. The resulting prediction equation: Y = 0.01 + 0.02X₁ − 0.11X₂ + 0.032X₃ + 0.08X₄ + 0.05X₅ + 0.03X₆ + 0.09X₇ demonstrated statistical significance (F = 10.327, p < 0.001), where X₁ to X₇ represent the prioritized technical components. Comprehensive validation over an eight-month period confirmed the model's reliability and practical applicability, with availability performance demonstrating significant improvement from 20% classified as "Very Severe" in January to 97% classified as "Very Good" in May. The study contributes to the limited body of knowledge on specialised healthcare facility maintenance management and provides hospital administrators with evidence-based tools for strategic decision-making, preventive maintenance planning, cost optimisation, and sustainable mortuary service delivery.

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Publication Details

Journal
International Journal of Advanced Research
Published
2025-08-14
DOI
https://doi.org/10.37284/ijar.8.1.3494
Citations
1
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
1.01
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article

Development of a Life Cycle Cost Analysis Model for Mortuary Buildings to Enhance Availability Performance: The Case Study of Musoma Municipal Council Hospital

Joseph Mkilania, Mahona Njigela
1 citations
International Journal of Advanced Research
BIM and Construction Integration
1.01
article

Development of a Life Cycle Cost Analysis Model for Mortuary Buildings to Enhance Availability Performance: The Case Study of Musoma Municipal Council Hospital

Joseph Mkilania, Mahona Njigela
article en
1 citations

Abstract

Healthcare facilities require comprehensive maintenance management strategies to ensure optimal service delivery and operational efficiency. This study developed a life cycle cost analysis (LCCA) model to improve maintenance management and availability performance of mortuary buildings, using Musoma Municipal Council Hospital as a case study. A mixed-methods research approach was adopted, involving comprehensive field observations, structured interviews, and systematic surveys with 36 participants representing diverse stakeholders, including engineers, administrators, technicians, mortuary staff, and healthcare professionals. Twelve technical factors influencing maintenance costs were systematically analysed using the Relative Importance Index (RII) methodology to establish priority rankings based on professional expertise and operational experience. The analysis revealed that electrical systems' reliability and backup power emerged as the most critical factor (RII = 0.931), followed by environmental control for chemical storage (RII = 0.923), and infection control and biosafety features (RII = 0.915). A robust multiple regression model was subsequently formulated using the seven highest-ranked factors, producing strong predictive outcomes with R² = 0.780, indicating that 78% of the variance in availability performance could be explained by the identified technical factors. The resulting prediction equation: Y = 0.01 + 0.02X₁ − 0.11X₂ + 0.032X₃ + 0.08X₄ + 0.05X₅ + 0.03X₆ + 0.09X₇ demonstrated statistical significance (F = 10.327, p < 0.001), where X₁ to X₇ represent the prioritized technical components. Comprehensive validation over an eight-month period confirmed the model's reliability and practical applicability, with availability performance demonstrating significant improvement from 20% classified as "Very Severe" in January to 97% classified as "Very Good" in May. The study contributes to the limited body of knowledge on specialised healthcare facility maintenance management and provides hospital administrators with evidence-based tools for strategic decision-making, preventive maintenance planning, cost optimisation, and sustainable mortuary service delivery.

International Journal of Advanced ResearchVol. 8(1)
Dar es Salaam Institute of Technology (TZ)
Openalex Percentile: Top 21%
BIM and Construction Integration
1.01
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