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This paper reflects on the challenges experienced within our own work and proposes solutions that may be useful to others attempting to collect, analyse, and compare cost data between public health research sites in low- and middle-income countries.
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On adding previous cost data, differences between the three systems decrease appreciably.
Cost data comparisons between the groups will be made using a bootstrap regression model (using 10,000 repetitions).
They could not find any significant difference between the cost data in the alternative periods.
Inconsistencies in methodology make it difficult to collect accurate cost data, and thus comparisons in between countries and healthcare systems are weak.
Cost data is based on sources assessed between 2012 and 2014, hence there is no need for adjusting unit costs.
There is a three-yearg delay between hospitals submitting cost data and these data being converted into prices, hence the t-3 subscript attached to these average costs.
This will first explore the relationship between patient level characteristics and costs (derived from a combination of cohort data with cost data) and then, taking this into account, between facility level characteristics and costs.
The economic costs to providers of treating malaria were based on detailed retrospective cost data from health facilities across the study sites between 2006 and 2007.
Fourth, although individual data were collected between 2005 and 2013, dietary cost data were derived with 2012 food price data.
There were no significant differences in baseline characteristics between patients with and without complete cost data.
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