Dataset Information

Health care during electricity failure: The hidden costs.

ABSTRACT: 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.

SUBMITTER: Mechtenberg A

PROVIDER: S-EPMC7641375 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Health care during electricity failure: The hidden costs.

Mechtenberg Abigail A McLaughlin Brady B DiGaetano Michael M Awodele Abigail A Omeeboh Leslie L Etwalu Emmanuel E Nanjula Lydia L Musaazi Moses M Shrime Mark M

PloS one 20201104 11

<h4>Background</h4>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.<h4>Methods</h4>Two methodologies were created to quantify these hidden costs. ...[more]

PMID: 33147212

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Project description:BACKGROUND AND OBJECTIVES:An understanding of the health care resource use associated with AKI is needed to frame the investment and cost-effectiveness of strategies to prevent AKI and promote kidney recovery. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:We assembled population-based cohort of adults hospitalized in Alberta between November of 2002 and March of 2009 without ESRD or an eGFR<15 ml/min per 1.73 m2. Outpatient serum creatinine measurements 6 months preceding admission defined baseline kidney function, and serum creatinine during the first 14 days of hospitalization defined Acute Kidney Injury Network stage; kidney recovery defined as serum creatinine within 25% of baseline and independence from dialysis was assessed at 90 days after AKI. Health care utilization and costs (in 2015 Canadian dollars) were determined from inpatient, outpatient, and physician claims datasets during the index hospitalization, recovery period (90 days post-AKI assessment), and 3-12 months post-AKI. A fully adjusted generalized linear model regression analysis was used to estimate costs associated with AKI. RESULTS:Of 239,906 hospitalized subjects, 25,495 (10.6%), 4598 (1.9%), 2493 (1.0%), and 670 (0.3%) had Acute Kidney Injury Network stages 1, 2, 3 without dialysis, and 3 with dialysis, respectively. Greater severity of AKI was associated with incremental increases in length of stay (+2.8; 95% confidence interval, 1.4 to 4.3 to +7.4; 95% confidence interval, 7.2 to 7.5 days) and costs (+$3779; 95% confidence interval, $3555 to $4004 to +$18,291; 95% confidence interval, $15,573 to $21,009 Canadian dollars) from admission to recovery assessment (3 months). At months 3-12 postadmission, compared with subjects without AKI, AKI with kidney recovery and AKI without kidney recovery were associated with incremental costs of +$2912-$3231 and +$6035-$8563 Canadian dollars, respectively. The estimated incremental cost of AKI in Canada is estimated to be over $200 million Canadian dollars per year. CONCLUSIONS:Severity of AKI, need for dialysis, and lack of kidney recovery are associated with significant health care costs in hospitalized patients and persist a year after admission. Strategies to identify, prevent, and facilitate kidney recovery are needed.

Project description:BackgroundLyme disease is the most frequently reported vector borne infection in the United States. The Centers for Disease Control have estimated that approximately 10% to 20% of individuals may experience Post-Treatment Lyme Disease Syndrome - a set of symptoms including fatigue, musculoskeletal pain, and neurocognitive complaints that persist after initial antibiotic treatment of Lyme disease. Little is known about the impact of Lyme disease or post-treatment Lyme disease symptoms (PTLDS) on health care costs and utilization in the United States.Objectives1) to examine the impact of Lyme disease on health care costs and utilization, 2) to understand the relationship between Lyme disease and the probability of developing PTLDS, 3) to understand how PTLDS may impact health care costs and utilization.MethodsThis study utilizes retrospective data on medical claims and member enrollment for persons aged 0-64 years who were enrolled in commercial health insurance plans in the United States between 2006-2010. 52,795 individuals treated for Lyme disease were compared to 263,975 matched controls with no evidence of Lyme disease exposure.ResultsLyme disease is associated with $2,968 higher total health care costs (95% CI: 2,807-3,128, p<.001) and 87% more outpatient visits (95% CI: 86%-89%, p<.001) over a 12-month period, and is associated with 4.77 times greater odds of having any PTLDS-related diagnosis, as compared to controls (95% CI: 4.67-4.87, p<.001). Among those with Lyme disease, having one or more PTLDS-related diagnosis is associated with $3,798 higher total health care costs (95% CI: 3,542-4,055, p<.001) and 66% more outpatient visits (95% CI: 64%-69%, p<.001) over a 12-month period, relative to those with no PTLDS-related diagnoses.ConclusionsLyme disease is associated with increased costs above what would be expected for an easy to treat infection. The presence of PTLDS-related diagnoses after treatment is associated with significant health care costs and utilization.

Dataset Information

Health care during electricity failure: The hidden costs.

Publications

Health care during electricity failure: The hidden costs.

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