Applicability of predictive models for 30-day unplanned hospital readmission risk in paediatrics: a systematic review.

OBJECTIVES: To summarise multivariable predictive models for 30-day unplanned hospital readmissions (UHRs) in paediatrics, describe their performance and completeness in reporting, and determine their potential for application in practice. DESIGN: Systematic review. DATA SOURCE: CINAHL, Embase and PubMed up to 7 October 2021. ELIGIBILITY CRITERIA: English or German language studies aiming to develop or validate a multivariable predictive model for 30-day paediatric UHRs related to all-cause, surgical conditions or general medical conditions were included. DATA EXTRACTION AND SYNTHESIS: Study characteristics, risk factors significant for predicting readmissions and information about performance measures (eg, c-statistic) were extracted. Reporting quality was addressed by the 'Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis' (TRIPOD) adherence form. The study quality was assessed by applying six domains of potential biases. Due to expected heterogeneity among the studies, the data were qualitatively synthesised. RESULTS: Based on 28 studies, 37 predictive models were identified, which could potentially be used for determining individual 30-day UHR risk in paediatrics. The number of study participants ranged from 190 children to 1.4 million encounters. The two most common significant risk factors were comorbidity and (postoperative) length of stay. 23 models showed a c-statistic above 0.7 and are primarily applicable at discharge. The median TRIPOD adherence of the models was 59% (P25-P75, 55%-69%), ranging from a minimum of 33% to a maximum of 81%. Overall, the quality of many studies was moderate to low in all six domains. CONCLUSION: Predictive models may be useful in identifying paediatric patients at increased risk of readmission. To support the application of predictive models, more attention should be placed on completeness in reporting, particularly for those items that may be relevant for implementation in practice.

Confirmatory versus explorative endpoint analysis: Decision-making on the basis of evidence available from market authorization and early benefit assessment for oncology drugs.

The early benefit assessment of pharmaceuticals in Germany and their preceding market authorization pursue different objectives. This is reflected by the inclusion of varying confirmatory endpoints within the evaluation of oncology drugs in early benefit assessment versus market authorization, with both relying on the same evidence. Data from assessments up to July 2015 are used to estimate the impact of explorative in comparison to confirmatory endpoints on market authorization and early benefit assessment by contrasting the benefit-risk ratio of EMA and the benefit-harm balance of the HTA jurisdiction. Agreement between market authorization and early benefit assessment is examined by Cohen's kappa (k). 21 of 41 assessments were considered in the analysis. Market authorization is more confirmatory than early benefit assessment because it includes a higher proportion of primary endpoints. The latter implies a primary endpoint to be relevant for the benefit-harm balance in only 67% of cases (0.078). Explorative mortality endpoints reached the highest agreement regarding the mutual consideration for the risk-benefit ratio and the benefit-harm balance (0.000). For explorative morbidity endpoints (-0.600), quality of life (-0.600) and side effects (-0.949) no agreement is ascertainable. To warrant a broader confirmatory basis for decisions supported by HTA, closer inter-institutional cooperation of approval authorities and HTA jurisdictions by means of reliable joint advice for manufacturers regarding endpoint definition would be favorable.