Variability in the use of pulse oximeters with children in Kenyan hospitals: A mixed-methods analysis

Abigail J Enoch, Mike English, the Clinical Information Network, Gerald McGivern and Sasha Shepperd

PLOS Medicine, 2019, vol. 16, issue 12, 1-20

Abstract: Background: Pulse oximetry, a relatively inexpensive technology, has the potential to improve health outcomes by reducing incorrect diagnoses and supporting appropriate treatment decisions. There is evidence that in low- and middle-income countries, even when available, widespread uptake of pulse oximeters has not occurred, and little research has examined why. We sought to determine when and with which children pulse oximeters are used in Kenyan hospitals, how pulse oximeter use impacts treatment provision, and the barriers to pulse oximeter use. Methods and findings: We analyzed admissions data recorded through Kenya’s Clinical Information Network (CIN) between September 2013 and February 2016. We carried out multiple imputation and generated multivariable regression models in R. We also conducted interviews with 30 healthcare workers and staff from 14 Kenyan hospitals to examine pulse oximetry adoption. We adapted the Integrative Model of Behavioural Prediction to link the results from the multivariable regression analyses to the qualitative findings. We included 27,906 child admissions from 7 hospitals in the quantitative analyses. The median age of the children was 1 year, and 55% were male. Three-quarters had a fever, over half had a cough; other symptoms/signs were difficulty breathing (34%), difficulty feeding (34%), and indrawing (32%). The most common diagnoses were pneumonia, diarrhea, and malaria: 45%, 35%, and 28% of children, respectively, had these diagnoses. Half of the children obtained a pulse oximeter reading, and of these, 10% had an oxygen saturation level below 90%. Children were more likely to receive a pulse oximeter reading if they were not alert (odds ratio [OR]: 1.30, 95% confidence interval (CI): 1.09, 1.55, p = 0.003), had chest indrawing (OR: 1.28, 95% CI: 1.17, 1.40, p

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pmed00:1002987

DOI: 10.1371/journal.pmed.1002987

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