Prevalence of malnutrition, obesity and nutritional risk of Australian paediatric inpatients: A national one-day snapshot

Aim Low prevalence rates of malnutrition at 2.5% to 4% have previously been reported in two tertiary paediatric Australian hospitals. The current study is the first to measure the prevalence of malnutrition, obesity and nutritional risk of paediatric inpatients in multiple hospitals throughout Australia. Methods Malnutrition, obesity and nutritional risk prevalence were investigated in 832 and 570 paediatric inpatients, respectively, in eight tertiary paediatric hospitals and eight regional hospitals across Australia on a single day. Malnutrition and obesity prevalence was determined using z-scores and body mass index (BMI) percentiles. High nutritional risk was determined as a Paediatric Yorkhill Malnutrition Score of 2 or more. Results The prevalence rates of malnourished, wasted, stunted, overweight and obese paediatric patients were 15%, 13.8%, 11.9%, 8.8% and 9.9%, respectively. Patients who identified as Aboriginal and Torres Strait Islander were more likely to have lower height-for-age z-scores (P < 0.01); however, BMI and weight-for-age z-scores were not significantly different. Children who were younger, from regional hospitals or with a primary diagnosis of cardiac disease or cystic fibrosis had significantly lower anthropometric z-scores (P = 0.05). Forty-four per cent of patients were identified as at high nutritional risk and requiring further nutritional assessment. Conclusions The prevalence of malnutrition and nutritional risk of Australian paediatric inpatients on a given day was much higher when compared with the healthy population. In contrast, the proportion of overweight and obese patients was less

Establishing a paediatric critical care core quality measure set using a multistakeholder, consensus-driven process

Introduction: Monitoring healthcare quality is challenging in paediatric critical care due to measure variability, data collection burden, and uncertainty regarding consumer and clinician priorities. Objective: We sought to establish a core quality measure set that (i) is meaningful to consumers and clinicians and (ii) promotes alignment of measure use and collection across paediatric critical care. Design: We conducted a multi-stakeholder Delphi study with embedded consumer prioritisation survey. The Delphi involved two surveys, followed by a consensus meeting. Triangulation methods were used to integrate survey findings prior tobefore the consensus meeting. In the consensus panel, broad agreement was reached on a core measure set, and recommendations were made for future measurement directions in paediatric critical care. Setting and participants: Australian and New Zealand paediatric critical care survivors (aged >18 years) and families were invited to rank measure priorities in an online survey distributed via social media and consumer groups. A concurrent Delphi study was undertaken with paediatric critical care clinicians, policy makers, and a consumer representative. Interventions: None. Main outcome measures: Priorities for quality measures. Results: Respondents to the consumer survey (n = 117) identified (i) nurse-patient ratios; (ii) visible patient goals; and (iii) long-term follow-up as their quality measure priorities. In the Delphi process, clinicians (Round 1 n = 191; Round 2 n = 117 [61% retention]; Round 3 n = 14) and a consumer representative reached broad agreement on a 51-item (61% of 83 initial measures) core measure set. Clinician priorities were (i) nurse-patient ratio; (ii) staff turnover; and (iii) long term-follow up. Measure feasibility was rated low due to a perceived lack of standardised case definitions or data collection burden. Five recommendations were generated. Conclusion(s): We defined a 51-item core measurement set for paediatric critical care, aligned with clinician and consumer priorities. Next steps are implementation and methodological evaluation in quality programs, and where appropriate, retirement of redundant measures.</p