ObjectivesWithin cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for selecting prevalence estimates. We aimed to compare different tools to assess the risk of bias of studies reporting prevalence, and develop and compare possible numerical scoring systems using these tools to set a threshold for inclusion of reports of prevalence in an economic analysis of neonatal hypoglycaemia.DesignAssessments of bias using two tools (Joanna Briggs Institute (JBI) Checklist for Prevalence Studies and a modified version of Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I)) were compared for 18 studies relevant to a single setting (neonatal hypoglycaemia). Inclusions of studies for use in a decision analysis model were considered based on summary scores derived from these tools.ResultsBoth tools were considered easy to use and produced dispersed scores for each of the 40 study–outcome combinations. The modified ROBINS-I scores were more skewed than the JBI scores, particularly at higher thresholds. The studies selected for inclusion are generally the same using either tool; if 50% was used as the cut-off threshold using the Applicable Score both tools would yield the same results. However, the JBI tool is shorter and may be easier to interpret and apply to studies that do not involve a control group, while the modified ROBINS-I tool assesses more methodological detail in studies that include a control group.ConclusionBoth tools performed well for systematically assessing studies that report on outcome prevalence and provided similar discrimination between studies for risk of bias. This convergent validity supports use of both tools for the purpose of assessing risk of bias and selecting studies that report prevalence for inclusion in economic analyses.

Australian New Zealand Clinical Trials Registry: ACTRN12608000623392.

No abstract

Background: Babies at risk of neonatal hypoglycaemia are often screened using cot-side glucometers, but non-enzymatic glucometers are inaccurate, potentially resulting in over-treatment and under-treatment, and low values require laboratory confirmation. More accurate enzymatic glucometers are available but at apparently higher costs. Objective: Our objective was to compare the cost of screening for neonatal hypoglycaemia using point-of-care enzymatic and non-enzymatic glucometers. Methods: We used a decision tree to model costs, including consumables and staff time. Sensitivity analyses assessed the impact of staff time, staff costs, probability that low results are confirmed via laboratory testing, false-positive and false-negative rates of non-enzymatic glucometers, and the blood glucose concentration threshold. Results: In the primary analysis, screening using an enzymatic glucometer cost NZD 86.94 (USD 63.47) while using a non-enzymatic glucometer cost NZD 97.08 (USD 70.87) per baby. Sensitivity analyses showed that using an enzymatic glucometer is cost saving with wide variations in staff time and costs, irrespective of the false-positive level of non-enzymatic glucometers, and where ≥78% of low values are laboratory confirmed. Where non-enzymatic glucometers may be less costly (e.g., false-negative rate exceeds 15%), instances of hypoglycaemia will be missed. Reducing the blood glucose concentration threshold to 1.94 mmol/L reduced the incidence of hypoglycaemia from 52 to 13%, and the cost of screening using a non-enzymatic glucometer to NZD 47.71 (USD 34.83). Conclusions: In view of their lower cost in most circumstances and greater accuracy, enzymatic glucometers should be routinely utilised for point-of-care screening for neonatal hypoglycaemia.

Background Neonatal hypoglycaemia is a common but treatable metabolic disorder that affects newborn infants and which, if not identified and treated adequately, may result in neurological sequelae that persist for the lifetime of the patient. The long-term financial and quality-of-life burden of neonatal hypoglycaemia has not been previously examined. Methods We assessed the postnatal hospital and long-term costs associated with neonatal hypoglycaemia over 80 year and 18 year time horizons, using a health-system perspective and assessing impact on quality of life using quality-adjusted life year (QALYs). A decision analytic model was used to represent key outcomes in the presence and absence of neonatal hypoglycaemia. Results The chance of developing one of the outcomes of neonatal hypoglycaemia in our model (cerebral palsy, learning disabilities, seizures, vision disorders) was 24.03% in subjects who experienced neonatal hypoglycaemia and 3.56% in those who do did not. Over an 80 year time horizon a subject who experienced neonatal hypoglycaemia had a combined hospital and post-discharge cost of NZ$72,000 due to the outcomes modelled, which is NZ$66,000 greater than a subject without neonatal hypoglycaemia. The net monetary benefit lost due to neonatal hypoglycaemia, using a value per QALY of NZ$43,000, is NZ$180,000 over an 80 year time horizon. Conclusions Even under the most conservative of estimates, neonatal hypoglycaemia contributes a significant financial burden to the health system both during childhood and over a lifetime. The combination of direct costs and loss of quality of life due to neonatal hypoglycaemia means that this condition warrants further research to focus on prevention and effective treatment.