Health care during electricity failure: The hidden costs.

BACKGROUND: Surgery risks increase when electricity is accessible but unreliable. During unreliable electricity events and without data on increased risk to patients, medical professionals base their decisions on anecdotal experience. Decisions should be made based on a cost-benefit analysis, but no methodology exists to quantify these risks, the associated hidden costs, nor risk charts to compare alternatives. METHODS: Two methodologies were created to quantify these hidden costs. In the first methodology through research literature and/or measurements, the authors obtained and analyzed a year's worth of hour-by-hour energy failures for four energy healthcare system (EHS) types in four regions (SolarPV in Iraq, Hydroelectric in Ghana, SolarPV+Wind in Bangladesh, and Grid+Diesel in Uganda). In the second methodology, additional patient risks were calculated according to time and duration of electricity failure and medical procedure impact type. Combining these methodologies, the cost from the Value of Statistical Lives lost divided by Energy shortage ($/kWh) is calculated for EHS type and region specifically. The authors define hidden costs due to electricity failure as VSL/E ($/kWh) and compare this to traditional electricity costs (always defined in $/kWh units), including Levelized Cost of Electricity (LCOE also in $/kWh). This is quantified into a fundamentally new energy healthcare system risk chart (EHS-Risk Chart) based on severity of event (probability of deaths) and likelihood of event (probability of electricity failure). RESULTS: VSL/E costs were found to be 10 to 10,000 times traditional electricity costs (electric utility or LCOE based). The single power source EHS types have higher risks than hybridized EHS types (especially as power loads increase over time), but all EHS types have additional risks to patients due to electricity failure (between 3 to 105 deaths per 1,000 patients). CONCLUSIONS: These electricity failure risks and hidden healthcare costs can now be calculated and charted to make medical decisions based on a risk chart instead of anecdotal experience. This risk chart connects public health and electricity failure using this adaptable, scalable, and verifiable model.

Fast Fourier Transformation of Peripheral Venous Pressure Changes More Than Vital Signs with Hemorrhage.

Vital signs are included in the determination of shock secondary to hemorrhage; however, more granular predictors are needed. We hypothesized that fast Fourier transformation (FFT) would have a greater percent change after hemorrhage than heart rate (HR) or systolic blood pressure (SBP). Using a porcine model, nine 17 kg pigs were hemorrhaged 10% of their calculated blood volume. Peripheral venous pressure waveforms, HR and SBP were collected at baseline and after 10% blood loss. FFT was performed on the peripheral venous pressure waveforms and the peak between 1 and 3 hertz (f1) corresponded to HR. To normalize values for comparison, percent change was calculated for f1, SBP, and HR. The mean percent change for f1 was an 18.8% decrease; SBP was a 3.31% decrease; and HR was a 0.95% increase. Using analysis of variance, FFT at f1 demonstrates a statistically significant greater change than HR or SBP after loss of 10% of circulating blood volume (p = 0.0023). Further work is needed to determine if this could be used in field triage to guide resuscitation.