Environmental impacts of healthcare services: Delivery of x-ray services

Esmaeili, Mohammad Amin; Twomey, Janet M.; Yildirim, Bayram; Overcash, Michael; Jahromi, Ashkan S.; Thomas, Nicholas J.; Mcadam, Ashlee; Dominquez, Fernando

doi:10.1109/issst.2011.5936905

Cited by 2 publications

(2 citation statements)

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“…Second, the outpatient facility uses a 12-h shift with a high utilization ratio of 72.5 percent due to scheduled appointments and high patient volume. For the hospital, an 8-h shift with 50 percent utilization was assumed in order to make the result comparable to other radiology LCA studies (Esmaeili et al , 2015; Esmaeili et al , 2011; Smith et al , 2014). The in-hospital energy use per patient has been plotted in Figure 7 for different levels of utilization.…”

Section: Resultsmentioning

confidence: 99%

“…Among these activities, the surgical and dialysis practices – because of the level of required energy and the magnitude of waste generation – and the outpatient service – mostly due to the potential carbon reduction of telemedicine – were targeted and quantified by healthcare scholars. Computed tomography and x-ray diagnostic imaging modalities have been evaluated recently by the life cycle methodology (Esmaeili et al , 2015; Smith et al , 2014; Esmaeili et al , 2011), but no life cycle assessment study for magnetic resonance imaging (MRI) diagnostic service was found in the literature. Here, a detailed accounting of energy and material use for MRI is presented.…”

Section: Introductionmentioning

confidence: 99%

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Environmental impact reduction as a new dimension for quality measurement of healthcare services

Esmaeili

McGuire

Overcash

et al. 2018

IJHCQA

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Purpose The purpose of this paper is to provide a detailed accounting of energy and materials consumed during magnetic resonance imaging (MRI). Design/methodology/approach The first and second stages of ISO standard (ISO 14040:2006 and ISO 14044:2006) were followed to develop life cycle inventory (LCI). The LCI data collection took the form of observations, time studies, real-time metered power consumption, review of imaging department scheduling records and review of technical manuals and literature. Findings The carbon footprint of the entire MRI service on a per-patient basis was measured at 22.4 kg CO2eq. The in-hospital energy use (process energy) for performing MRI is 29 kWh per patient for the MRI machine, ancillary devices and light fixtures, while the out-of-hospital energy consumption is approximately 260 percent greater than the process energy, measured at 75 kWh per patient related to fuel for generation and transmission of electricity for the hospital, plus energy to manufacture disposable, consumable and reusable products. The actual MRI and standby energy that produces the MRI images is only about 38 percent of the total life cycle energy. Research limitations/implications The focus on methods and proof-of-concept meant that only one facility and one type of imaging device technology were used to reach the conclusions. Based on the similar studies related to other imaging devices, the provided transparent data can be generalized to other healthcare facilities with few adjustments to utilization ratios, the share of the exam types, and the standby power of the facilities’ imaging devices. Practical implications The transparent detailed life cycle approach allows the data from this study to be used by healthcare administrators to explore the hidden public health impact of the radiology department and to set goals for carbon footprint reductions of healthcare organizations by focusing on alternative imaging modalities. Moreover, the presented approach in quantifying healthcare services’ environmental impact can be replicated to provide measurable data on departmental quality improvement initiatives and to be used in hospitals’ quality management systems. Originality/value No other research has been published on the life cycle assessment of MRI. The share of outside hospital indirect environmental impact of MRI services is a previously undocumented impact of the physician’s order for an internal image.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%