Asset Condition Assessment Model for Healthcare Facilities

Dalia Salem, Purdue University


The healthcare industry accounts for one-seventh of the U.S. gross national product (GNP). U.S. healthcare spending exceeded $3.6 trillion in 2013 and $4 trillion in 2016. Accordingly, improving the efficiency of the public healthcare sector has the potential to be one of the most cost-effective management solutions. Poor healthcare environments cost the U.S. tens of billions of dollars annually. There are several factors that influence the critical assets of healthcare facilities, including the physical condition of the facility, infection prevention, life safety, and revenue loss. The aim of this research is to develop an asset condition assessment model for healthcare facility asset criticality that guides decision making related to capital renewal needs. This model will improve the asset management of healthcare buildings, one of the largest national infrastructure sectors. The framework of the asset condition assessment (ACA) critical rating model consists of four main factors: Physical, Environmental, General Safety, and Revenue Loss. These factors were broken down into 12 subfactors. This tool will improve the asset management of healthcare facilities. The data were collected in two sources. The first part was an expert-based survey. In part two, the real project data of 10 mechanical, electrical & plumbing (MEP) asset types were collected from 16 Indiana hospitals for a total of 707 assets. The data were used to develop the Asset Condition Assessment (ACA) critical rating model. Two modeling techniques were used to predict and assess the critical asset ratings based on various factors. Patient risk space groups and asset redundancy were the main factors considered by the developed ACA model. The first approach used to calculate the weighting criteria of the factors was the Analytic Hierarchy Process (AHP). The General Safety factor had the highest weight of the main factors (31%), followed by Environmental considerations (27%). The second model was developed based on the integration of the AHP and Regression Analysis techniques to evaluate the asset condition criticality of healthcare facilities. The integrated model was verified and then validated via mathematical and visual validation means. Validation results showed the robustness of the developed ACA critical rating model (88.32%). This represents a solid model and satisfactory results. This research developed a numerical asset condition assessment (ACA) critical rating scale. The scale was divided into five categories (Very Good, Good, Fair, Critical and Very Critical) ranging from 0 to 10. Each category was identified in terms of the rating range number, associated condition, and actions needed. The developed scale has the potential to guide capital renewals leaders in predicting and managing the critical infrastructure needs of healthcare facilities and to help plan the required asset actions.




Elwakil, Purdue University.

Subject Area

Health care management

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