Modeling the performance of healthcare construction projects

Healthcare-sector projects are some of the most complex in modern practice due to their reliance on high-tech components and the level of precision they must maintain. Existing literature in healthcare performance specifically is scarce, but there is a recent increasing trend in both healthcare construction and a corresponding trend in related literature. No previously existing study has derived weights (relative importance) of performance metric in an objective, data-based manner. The purpose of this paper is to present a newly developed mathematical model that derives these weights, free of subjectivity that is common in other literature.,This paper’s model considers 17 exceptional projects and 19 average projects, and reveals the weights (or relative importance) of ten performance metrics by comparing how projects relate to one another in terms of each metric individually. It solves an eigenvalue problem that maximizes the difference between average and exceptional project performances.,The most significant weight, i.e. the performance metric which has the greatest impact on healthcare project performance, was request for information per million dollars with a weight of 16.07 percent. Other highly weighted metrics included construction speed and schedule growth at 13.08 and 12.23 percent, respectively. Rework was the least significant metric at 3.61 percent, but not all metrics of quality had low ratings. Deficiency issues per million dollars was weighted at 11.61 percent, for example. All weights derived by the model in this paper were validated statistically to ensure their applicability as comparison and assessment tools.,There is no widely accepted measure of project performance specific to healthcare construction. This study’s contribution to the body of knowledge is its mathematical model which is a landmark effort to develop a single, objective, unified project performance index for healthcare construction. Furthermore, this unified score presents a user-friendly avenue for contractors to standardize their productivity tracking – a missing piece in the practices of many contractors.

[1]  Robert Ries,et al.  Construction Delivery Systems: A Comparative Analysis of Their Performance within School Districts , 2006 .

[2]  Albert P.C. Chan,et al.  Factors Affecting the Success of a Construction Project , 2004 .

[3]  Ben F. Bigelow,et al.  Comparison of Construction Manager at Risk and Integrated Project Delivery Performance on Healthcare Projects: A Comparative Case Study , 2015 .

[4]  C. William Ibbs,et al.  Project delivery systems and project change: Quantitative analysis , 2003 .

[5]  Eddy M. Rojas,et al.  Comparative Analysis of Project Delivery Systems Cost Performance in Pacific Northwest Public Schools , 2008 .

[6]  Awad S. Hanna,et al.  Request for Information: Benchmarks and Metrics for Major Highway Projects , 2012 .

[7]  C. Camargo,et al.  US population aging and demand for inpatient services. , 2014, Journal of hospital medicine.

[8]  K. N. Jha,et al.  Critical Factors Affecting Quality Performance in Construction Projects , 2006 .

[9]  Ehsan Asnaashari,et al.  Identifying Success Factors of Healthcare Facility Construction Projects in Iran , 2016 .

[10]  Awad S. Hanna,et al.  The impact of change orders on mechanical construction labour efficiency , 1999 .

[11]  D. Štreimikienė,et al.  A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency , 2017 .

[12]  Mohsin K. Siddiqui,et al.  Role of Communication and Coordination in Project Success: Case Study , 2015 .

[13]  Awad S. Hanna,et al.  Quantifying Performance for the Integrated Project Delivery System as Compared to Established Delivery Systems , 2013 .

[14]  Bryan Franz,et al.  Project Impacts of Specialty Mechanical Contractor Design Involvement in the Health Care Industry: Comparative Case Study , 2013 .

[15]  Alfred E. Thal,et al.  Analysis of the Design-Build Delivery Method in Air Force Construction Projects , 2009 .