Evidence map›Paper›PMID 33147212›Full record

ArticlePloS one2020

Health care during electricity failure: The hidden costs.

Abigail Mechtenberg, Brady McLaughlin, Michael DiGaetano, Abigail Awodele, Leslie Omeeboh, Emmanuel Etwalu, Lydia Nanjula, Moses Musaazi, Mark Shrime

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Assessing the impacts of sufficient and reliable electricity in low-resource healthcare facilities.Proceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Abigail MechtenbergCenter for Sustainable Energy, University of Notre Dame, South Bend, Indiana, United States of America.ORCID 0000-0001-7893-6181
Brady McLaughlinCenter for Sustainable Energy, University of Notre Dame, South Bend, Indiana, United States of America.
Michael DiGaetanoCenter for Sustainable Energy, University of Notre Dame, South Bend, Indiana, United States of America.ORCID 0000-0002-8614-9898
Abigail AwodeleCenter for Sustainable Energy, University of Notre Dame, South Bend, Indiana, United States of America.
Leslie OmeebohCenter for Sustainable Energy, University of Notre Dame, South Bend, Indiana, United States of America.
Emmanuel EtwaluCollege of Engineering, Design, Art, and Technology (CEDAT), Makerere University, Kampala, Uganda.
Lydia NanjulaMulago Hospital, Kampala, Uganda.
Moses MusaaziCollege of Engineering, Design, Art, and Technology (CEDAT), Makerere University, Kampala, Uganda.
Mark ShrimeHarvard Medical School, Harvard University, Boston, MA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgery 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.

methodsTwo 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).

resultsVSL/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).

conclusionsThese 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.

Indexed as

Health Care CostsBangladeshClinical Decision-MakingCost-Benefit AnalysisElectric Power SuppliesGhanaHumansIraqUganda

Identifiers

PMID33147212
PMCPMC7641375

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.